U.S. patent application number 14/542019 was filed with the patent office on 2016-04-07 for systems and methods for updating data across multiple network architectures.
The applicant listed for this patent is Google Inc.. Invention is credited to Jay D. Logue, Matthew G. Neeley, Zachary B. Smith.
Application Number | 20160099826 14/542019 |
Document ID | / |
Family ID | 55487513 |
Filed Date | 2016-04-07 |
United States Patent
Application |
20160099826 |
Kind Code |
A1 |
Logue; Jay D. ; et
al. |
April 7, 2016 |
SYSTEMS AND METHODS FOR UPDATING DATA ACROSS MULTIPLE NETWORK
ARCHITECTURES
Abstract
A method for updating a storage element may include receiving a
first set of data from a first device that operating in a
structure. The first set of data corresponds to a first data type
interpretable by the first device. The method may also include
translating the first set of data into a second set of data of a
second data type interpretable by a second device operating in the
structure but not by the first device. The first set of data and
the second set of data are associated with a first portion of
information associated with occupancy properties of the structure.
The method may then include storing the second set of data in a
storage element that includes a second portion information
associated with the occupancy properties of the structure.
Inventors: |
Logue; Jay D.; (San Jose,
CA) ; Smith; Zachary B.; (San Francisco, CA) ;
Neeley; Matthew G.; (San Mateo, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google Inc. |
Mountain View |
CA |
US |
|
|
Family ID: |
55487513 |
Appl. No.: |
14/542019 |
Filed: |
November 14, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14508884 |
Oct 7, 2014 |
|
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14542019 |
|
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Current U.S.
Class: |
709/223 |
Current CPC
Class: |
G06F 16/258 20190101;
G06F 16/84 20190101; H04L 41/04 20130101; G06F 16/22 20190101; H04L
67/10 20130101; H04L 2012/285 20130101; G06F 40/151 20200101; G06F
40/14 20200101; G06F 16/122 20190101; H04L 67/02 20130101; H04L
12/2825 20130101 |
International
Class: |
H04L 12/24 20060101
H04L012/24; H04L 12/26 20060101 H04L012/26 |
Claims
1. A non-transitory computer-readable medium comprising
instructions configured to: receive JavaScript Object Notation
(JSON) format data from a first device configured to monitor or
control a first condition associated with heating, ventilating, and
air conditioning (HVAC) properties in a home or office environment;
receive tag-length-value (TLV) format data from a second device
configured to monitor or control a second condition in the home or
office environment; identify a first bucket in a storage element
based on the JSON format data, wherein the storage element
comprises a first plurality of buckets associated with the first
device and a second plurality of buckets associated with the second
device, wherein each bucket of the first and second pluralities of
buckets is defined according to a JSON protocol and is associated
with a data type that groups two or more data objects together
according to a common field; write the JSON format data into the
first bucket; translate the TLV-format data into an equivalent JSON
format data, wherein translation of the TLV-format data into the
equivalent JSON format data includes: identifying a value field of
the TLV-format data in a translation dictionary comprising a
plurality of mappings between a plurality of tags associated with
the TLV-format data and a plurality of bucket keys associated with
the first and second pluralities of buckets; and determining a
bucket value in the equivalent JSON-format data based on the value
field and customized mappings between a plurality of value fields
of the TLV-format data and a plurality of bucket values in the
JSON-format data; identify a second bucket of the second plurality
of buckets in the storage element based on the bucket value; write
the equivalent JSON format data into the second bucket; and adjust
the HVAC properties in the home or office environment by adjusting
an operation of the first device based on the JSON format data
written in the first bucket and the equivalent JSON format data
written in the second bucket.
2. The non-transitory computer-readable medium of claim 1, wherein
the first bucket and the second bucket comprises information
organized in a field-value pair.
3. The non-transitory computer-readable medium of claim 1, wherein
the instructions configured to translate the TLV-format data into
the equivalent JSON-format data comprises using data represented in
the value field of the TLV-format data as the bucket value in the
equivalent JSON-format data.
4. (canceled)
5. (canceled)
6. The non-transitory computer-readable medium of claim 1, wherein
the instructions configured to translate the TLV-format data into
the equivalent JSON-format data comprises: identifying a profile
identification associated with the TLV-format data; and determining
a bucket key that corresponds to the profile identification based
on the translation dictionary comprising a plurality of customized
mappings between a plurality of profile identifications associated
with the TLV-format data and the plurality of bucket keys
associated with the JSON-format data.
7. The non-transitory computer-readable medium of claim 6, wherein
the profile identification corresponds to a type of device.
8. A method, comprising: receiving, via at least one processor,
JavaScript Object Notation (JSON) format data from a first device
configured to monitor or control a first condition associated with
heating, ventilating, and air conditioning (HVAC) properties in a
home or office environment; receiving a tag-length-value (TLV)
format data from a second device configured to monitor or control a
second condition in the home or office environment; identifying a
first bucket in a storage element based on the JSON format data,
wherein the storage element comprises a first plurality of buckets
associated with the first device and a second plurality of buckets
associated with the second device, wherein each bucket of the first
and second pluralities of buckets is defined according to a JSON
protocol and is associated with a data type that groups two or more
data objects together according to a common field; writing the JSON
format data into the first bucket; translating the TLV-format data
into an equivalent JSON format data, wherein translation of the
TLV-format data into the equivalent JSON format data includes:
identifying a value field of the TLV-format data in a translation
dictionary comprising a plurality of mappings between a plurality
of tags associated with the TLV-format data and a plurality of
bucket keys associated with the first and second pluralities of
buckets; and determining a bucket value in the equivalent
JSON-format data based on the value field and customized mappings
between a plurality of value fields of the TLV-format data and a
plurality of bucket values in the JSON-format data; identifying a
second bucket of the second plurality of buckets in the storage
element based on the bucket value; writing the equivalent JSON
format data into the second bucket; and adjust the HVAC properties
in the home or office environment by adjusting an operation of the
first device based on the JSON format data written in the first
bucket and the equivalent JSON format data written in the second
bucket.
9. The method of claim 8, wherein translating the TLV format data
into the equivalent JSON format data comprises identifying an
equivalent representation of the TLV format data using translation
dictionary.
10. (canceled)
11. The method of claim 8, wherein updating the second bucket in
the storage element comprises: determining a bucket key that
corresponds to the second bucket in the storage element based on
the equivalent JSON format data, wherein the bucket key is
configured to identify the second bucket; determining a bucket
identifier that corresponds to an instance of the second bucket
based on the equivalent JSON format data; and writing the bucket
value into the second bucket based on the equivalent JSON format
data.
12. The method of claim 8, comprising sending the equivalent JSON
format data to the first device.
13. A system comprising: a first device and a second device
configured to communicate with each other using a tag-length-field
(TLV) data format, wherein the first device and the second device
are configured to control or monitor conditions in a home
environment, wherein the first device is configured to control
conditions associated with heating, ventilating, and air
conditioning (HVAC) properties in the home environment; a storage
element configured to store information associated with the first
device and the second device in a JavaScript Object Notation (JSON)
data format, wherein the storage element comprises a first
plurality of buckets associated with the first device and a second
plurality of buckets associated with the second device, wherein
each bucket of the first and second pluralities of buckets is
defined according to a JSON protocol and is associated with a data
type that groups two or more data objects together according to a
common field; and a cloud-computing device configured to update the
storage element by: receiving a first set of data from the first
device, wherein the first set of data corresponds to the JSON
format data; receiving a second set of data from the second device,
wherein the second set of data corresponds to the TLV format data;
identifying a first bucket in the storage element based on the
first set of data; writing the first set of data into the first
bucket; translating the second set of data into a third set of data
having the JSON data format, wherein translation of the second set
of data into the third set of data includes: identifying a value
field of the second set of data in a translation dictionary
comprising a plurality of mappings between a plurality of tags
associated with the TLV-format data and a plurality of bucket keys
associated with the first and second pluralities of buckets; and
determining a bucket value in the third set of data based on the
value field and customized mappings between a plurality of value
fields of the TLV-format data and a plurality of bucket values in
the JSON-format data; identifying a second bucket in the storage
element based on the bucket value; writing the third set of data
into the second bucket; and adjusting the HVAC properties in the
home environment by adjusting an operation of the first device
based on the first set of data written in the first bucket and the
third set of data written in the second bucket.
14. (canceled)
15. The system of claim 13, wherein the plurality of mappings is
input into the translation dictionary as a customized mapping.
16. The system of claim 13, wherein the cloud-computing device is
configured to translate the second set of data into the third set
of data by: identifying a profile identification associated with a
tag field in the second set of data; and determining a bucket key
that corresponds to the profile identification based on the
translation dictionary.
17. The system of claim 16, wherein the profile identification
corresponds to a type of second device.
18. The system of claim 17, wherein the type of second device
comprises a thermostat, a hazard detector, or a portable electronic
device.
19. The system of claim 16, wherein the bucket key corresponds to a
bucket associated with the storage element.
20. The system of claim 13, wherein the cloud-computing device is
configured to translate the second set of data into the third set
of data by: identifying an instance identification associated with
a tag field in the second set of data; and determining a bucket
identifier that corresponds to the instance identification based on
the translation dictionary, wherein the bucket identifier
corresponds to an instance of a bucket associated with the storage
element.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a Continuation Application of, and
claims priority to, U.S. patent application Ser. No. 14/508,884,
filed Oct. 7, 2014, entitled "Systems and Methods for Updating Data
Across Multiple Network Architectures," the entirety of which is
incorporated by reference herein for all purposes.
BACKGROUND
[0002] The present disclosure relates generally to converting data
for use across multiple network architectures. More specifically,
the present disclosure relates generally to converting different
types of data received by multiple network architectures into one
uniform format, such that the data from all of the multiple network
architectures may be interpreted together.
[0003] Network-connected devices appear throughout homes. Some
devices are often capable of communicating with each other through
a single network type (e.g., WiFi connection) using one type of
transfer protocol, while other devices communicate with each other
through another network type using a different type of transfer
protocol. Since different devices disposed in the same home may be
connected to different protocols, each device in the home may not
be able to communicate with all of the devices in the home.
[0004] This section is intended to introduce the reader to various
aspects of art that may be related to various aspects of the
present techniques, which are described and/or claimed below. This
discussion is believed to be helpful in providing the reader with
background information to facilitate a better understanding of the
various aspects of the present disclosure. Accordingly, it should
be understood that these statements are to be read in this light,
and not as admissions of prior art.
SUMMARY
[0005] A summary of certain embodiments disclosed herein is set
forth below. It should be understood that these aspects are
presented merely to provide the reader with a brief summary of
these certain embodiments and that these aspects are not intended
to limit the scope of this disclosure. Indeed, this disclosure may
encompass a variety of aspects that may not be set forth below.
[0006] In one embodiment, a method for updating a storage element
may include receiving a first set of data from a first set of
devices that operates within a home environment. The first set of
data corresponds to a first data type. The method may also include
translating the first set of data into a second set of data having
a second data type, such that the second data type is interpretable
by a second set of devices that operates within the home
environment. The method may then include storing the second set of
data in the storage element.
[0007] In another embodiment, a system may include a first set of
devices that communicates with each other using a tag-length-field
(TLV) data format and a second set of devices that communicates
with each other using a JavaScript Object Notation (JSON) data
format. The first and second set of devices control or monitor
conditions in a home environment. The system may also include a
storage element that stores information associated with the first
and second sets of devices in the JSON data format. The system may
also include a cloud-computing device that updates the storage
element by receiving a first set of data from the first set of
devices, translating the first set of data into a second set of
data having the JSON data format, and storing the second set of
data in the storage element.
[0008] In yet another embodiment, a non-transitory
computer-readable medium may include instructions to receive
JavaScript Object Notation (JSON) format data from a first device
that monitors or controls a first condition in a home or office
environment and receive tag-length-value (TLV) format data from a
second device that monitors or controls a second condition in the
home or office environment. The instructions may then update a
first bucket in a storage element based on the JSON format data,
translate the TLV-format data into an equivalent JSON format data,
and update a second bucket in the storage element based on the
equivalent format data.
[0009] Various refinements of the features noted above may exist in
relation to various aspects of the present disclosure. Further
features may also be incorporated in these various aspects as well.
These refinements and additional features may exist individually or
in any combination. For instance, various features discussed below
in relation to one or more of the illustrated embodiments may be
incorporated into any of the above-described aspects of the present
disclosure alone or in any combination. The brief summary presented
above is intended only to familiarize the reader with certain
aspects and contexts of embodiments of the present disclosure
without limitation to the claimed subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] Various aspects of this disclosure may be better understood
upon reading the following detailed description and upon reference
to the drawings in which:
[0011] FIG. 1 illustrates a block diagram of a general device that
may control and/or monitor a building environment, in accordance
with an embodiment;
[0012] FIG. 2 illustrates a block diagram of a smart-home
environment in which the general device of FIG. 1 may communicate
with other devices via a network layer protocol, in accordance with
an embodiment;
[0013] FIG. 3 illustrates a network-level view of an extensible
devices and services platform with which the smart-home environment
of FIG. 2 can be integrated, in accordance with an embodiment;
[0014] FIG. 4 illustrates an abstracted functional view of the
extensible devices and services platform of FIG. 3, with reference
to a processing engine as well as devices of the smart-home
environment, in accordance with an embodiment;
[0015] FIG. 5 illustrates a block diagram of communication system
used to communicate between various types of devices and a
cloud-computing system that may include the extensible devices and
services platform of FIG. 3, in accordance with an embodiment;
[0016] FIG. 6 illustrates an example of a network-based
communication system that may use a JavaScript Object Notation
(JSON) based communication protocol to communicate between devices
in the smart-home environment of FIG. 2, in accordance with an
embodiment;
[0017] FIG. 7 illustrates the network-based communication system of
FIG. 6 together with buckets of information provided at each of the
entities of that system, in accordance with an embodiment;
[0018] FIG. 8 illustrates the network-based communication system of
FIG. 6 with some simplified components of a remote server, in
accordance with an embodiment;
[0019] FIG. 9 illustrates example buckets of information that may
be part of a storage element in the remote server depicted in FIG.
8, in accordance with an embodiment;
[0020] FIG. 10 illustrates a block diagram of an Open Systems
Interconnection (OSI) model that depicts functions of a
communication system employed by the devices in the smart-home
environment of FIG. 2, in accordance with an embodiment;
[0021] FIG. 11 illustrates a block diagram detailing
characteristics of an efficient low power wireless personal network
(ELoWPAN) in light of the application layer, transport layer, and
network layer of the Open Systems Interconnection (OSI) model of
FIG. 10, in accordance with an embodiment;
[0022] FIG. 12 illustrates a diagram of a service communicating
with fabrics of devices via the ELoWPAN communication system of
FIG. 11, in accordance with an embodiment;
[0023] FIG. 13 illustrates an embodiment of a communication between
two devices in the smart-home environment of FIG. 2, in accordance
with an embodiment;
[0024] FIG. 14 illustrates a block diagram of an embodiment of a
tag-length-value (TLV) packet that may be used in the communication
of FIG. 12, in accordance with an embodiment;
[0025] FIG. 15 illustrates a block diagram of communication system
used to translate data received from various types of devices, in
accordance with an embodiment; and
[0026] FIG. 16 illustrates a flow chart of a method for translating
TLV-format data received from various devices in the smart-home
environment of FIG. 2 into JSON-format data, in accordance with an
embodiment.
DETAILED DESCRIPTION
[0027] One or more specific embodiments of the present disclosure
will be described below. These described embodiments are only
examples of the presently disclosed techniques. Additionally, in an
effort to provide a concise description of these embodiments, all
features of an actual implementation may not be described in the
specification. It should be appreciated that in the development of
any such actual implementation, as in any engineering or design
project, numerous implementation-specific decisions must be made to
achieve the developers' specific goals, such as compliance with
system-related and business-related constraints, which may vary
from one implementation to another. Moreover, it should be
appreciated that such a development effort might be complex and
time consuming, but may nevertheless be a routine undertaking of
design, fabrication, and manufacture for those of ordinary skill
having the benefit of this disclosure.
[0028] When introducing elements of various embodiments of the
present disclosure, the articles "a," "an," and "the" are intended
to mean that there are one or more of the elements. The terms
"comprising," "including," and "having" are intended to be
inclusive and mean that there may be additional elements other than
the listed elements. Additionally, it should be understood that
references to "one embodiment" or "an embodiment" of the present
disclosure are not intended to be interpreted as excluding the
existence of additional embodiments that also incorporate the
recited features.
[0029] Embodiments disclosed herein are related to storing data
received from various devices in a smart-home environment in one
format, such that the data may be analyzed or interpreted
consistently by each device or by some other entity (e.g., cloud
service). Generally, some devices may send updates to a cloud-based
service or a cloud-computing system in a JavaScript Object Notation
(JSON) format. The JSON-format data may identify a particular
bucket of a database accessible by the cloud-based service to
update. The JSON-format data may also indicate a new value to
update the identified bucket of the database. As a result, the
cloud-computing system may store data received from various devices
in an organized fashion, such that the stored data may be easily
retrieved, analyzed, processed, and the like.
[0030] Although certain devices may communicate with the
cloud-computing system using JSON-format data, other devices may
communicate using tag-length-value (TLV) format data, which may be
communicated in a more efficient manner as compared to JSON-format
data. As such, to update a database that stores JSON-format data,
the cloud-computing system may translate the received TLV-format
data into an equivalent JSON-format data and update a corresponding
bucket in the database using the equivalent JSON-format data. As a
result, the database may be accurately updated to include a status
or state of each type of JSON-enabled device and TLV-enabled
device.
Smart Device in Smart Home Environment
[0031] By way of introduction, FIG. 1 illustrates an example of a
general device 10 that may that may be disposed within a building
environment. In one embodiment, the device 10 may include one or
more sensors 12, a user-interface component 14, a power supply 16
(e.g., including a power connection and/or battery), a network
interface 18, a high-power processor 20, a low-power processor 22,
a light source 26, and the like.
[0032] The sensors 12, in certain embodiments, may detect various
properties such as acceleration, temperature, humidity, water,
supplied power, proximity, external motion, device motion, sound
signals, ultrasound signals, light signals, fire, smoke, carbon
monoxide, global-positioning-satellite (GPS) signals,
radio-frequency (RF), other electromagnetic signals or fields, or
the like. As such, the sensors 12 may include temperature
sensor(s), humidity sensor(s), hazard-related sensor(s) or other
environmental sensor(s), accelerometer(s), microphone(s), optical
sensors up to and including camera(s) (e.g., charged coupled-device
or video cameras), active or passive radiation sensors, GPS
receiver(s) or radiofrequency identification detector(s). While
FIG. 1 illustrates an embodiment with a single sensor, many
embodiments may include multiple sensors. In some instances, the
device 10 may includes one or more primary sensors and one or more
secondary sensors. Here, the primary sensor(s) may sense data
central to the core operation of the device (e.g., sensing a
temperature in a thermostat or sensing smoke in a smoke detector),
while the secondary sensor(s) may sense other types of data (e.g.,
motion, light or sound), which can be used for energy-efficiency
objectives or smart-operation objectives.
[0033] One or more user-interface components 14 in the device 10
may receive input from the user and/or present information to the
user. The received input may be used to determine a setting. In
certain embodiments, the user-interface components may include a
mechanical or virtual component that responds to the user's motion.
For example, the user can mechanically move a sliding component
(e.g., along a vertical or horizontal track) or rotate a rotatable
ring (e.g., along a circular track), or the user's motion along a
touchpad may be detected. Such motions may correspond to a setting
adjustment, which can be determined based on an absolute position
of a user-interface component 14 or based on a displacement of a
user-interface components 14 (e.g., adjusting a set point
temperature by 1 degree F. for every 10.degree. rotation of a
rotatable-ring component). Physically and virtually movable
user-interface components can allow a user to set a setting along a
portion of an apparent continuum. Thus, the user may not be
confined to choose between two discrete options (e.g., as would be
the case if up and down buttons were used) but can quickly and
intuitively define a setting along a range of possible setting
values. For example, a magnitude of a movement of a user-interface
component may be associated with a magnitude of a setting
adjustment, such that a user may dramatically alter a setting with
a large movement or finely tune a setting with a small
movement.
[0034] The user-interface components 14 may also include one or
more buttons (e.g., up and down buttons), a keypad, a number pad, a
switch, a microphone, and/or a camera (e.g., to detect gestures).
In one embodiment, the user-interface component 14 may include a
click-and-rotate annular ring component that may enable the user to
interact with the component by rotating the ring (e.g., to adjust a
setting) and/or by clicking the ring inwards (e.g., to select an
adjusted setting or to select an option). In another embodiment,
the user-interface component 14 may include a camera that may
detect gestures (e.g., to indicate that a power or alarm state of a
device is to be changed). In some instances, the device 10 may have
one primary input component, which may be used to set a plurality
of types of settings. The user-interface components 14 may also be
configured to present information to a user via, e.g., a visual
display (e.g., a thin-film-transistor display or organic
light-emitting-diode display) and/or an audio speaker.
[0035] The power-supply component 16 may include a power connection
and/or a local battery. For example, the power connection may
connect the device 10 to a power source such as a line voltage
source. In some instances, an AC power source can be used to
repeatedly charge a (e.g., rechargeable) local battery, such that
the battery may be used later to supply power to the device 10 when
the AC power source is not available.
[0036] The network interface 18 may include a component that
enables the device 10 to communicate between devices, servers,
routers, and the like. As such, the network interface 18 may enable
the device 10 to communicate with other devices 10 or
communication-capable components via a wired or wireless network.
The network interface 18 may include a wireless card or some other
transceiver connection to facilitate this communication. In any
case, the network interface 18 may be capable of communicating with
a cloud-computing system that may receive data from a variety of
different types of devices 10, each of which may communicate using
a different communication protocol. As will be appreciated, the
cloud-computing system may include certain components that enable
it to translate the data received from each different type of
device into one data format. Additional details regarding the
translation of data by the cloud-computing device will be described
below.
[0037] The high-power processor 20 and the low-power processor 22
may support one or more of a variety of different device
functionalities. As such, the high-power processor 20 and the
low-power processor 22 may each include one or more processors
configured and programmed to carry out and/or cause to be carried
out one or more of the functionalities described herein. In one
embodiment, the high-power processor 20 and the low-power processor
22 may include general-purpose processors carrying out computer
code stored in local memory (e.g., flash memory, hard drive, random
access memory), special-purpose processors or application-specific
integrated circuits, combinations thereof, and/or using other types
of hardware/firmware/software processing platforms. In certain
embodiments, the high-power processor 20 may execute
computationally intensive operations such as operating the
user-interface component 14 and the like. The low-power processor
22, on the other hand, may manage less complex processes such as
detecting a hazard or temperature from the sensor 12. In one
embodiment, the low-power processor may wake or initialize the
high-power processor for computationally intensive processes.
[0038] By way of example, the high-power processor 20 and the
low-power processor 22 may detect when a location (e.g., a house or
room) is occupied (i.e., includes a presence of a human), up to and
including whether it is occupied by a specific person or is
occupied by a specific number of people (e.g., relative to one or
more thresholds). In one embodiment, this detection can occur,
e.g., by analyzing microphone signals, detecting user movements
(e.g., in front of a device), detecting openings and closings of
doors or garage doors, detecting wireless signals, detecting an
internet protocol (IP) address of a received signal, detecting
operation of one or more devices within a time window, or the like.
Moreover, the high-power processor 20 and the low-power processor
22 may include image recognition technology to identify particular
occupants or objects.
[0039] In some instances, the high-power processor 20 may predict
desirable settings and/or implement those settings. For example,
based on the presence detection, the high-power processor 20 may
adjust device settings to, e.g., conserve power when nobody is home
or in a particular room or to accord with user preferences (e.g.,
general at-home preferences or user-specific preferences). As
another example, based on the detection of a particular person,
animal or object (e.g., a child, pet or lost object), the
high-power processor 20 may initiate an audio or visual indicator
of where the person, animal or object is or may initiate an alarm
or security feature if an unrecognized person is detected under
certain conditions (e.g., at night or when lights are off).
[0040] In some instances, devices may interact with each other such
that events detected by a first device influences actions of a
second device. For example, a first device can detect that a user
has entered into a garage (e.g., by detecting motion in the garage,
detecting a change in light in the garage or detecting opening of
the garage door). The first device can transmit this information to
a second device via the network interface 18, such that the second
device can, e.g., adjust a home temperature setting, a light
setting, a music setting, and/or a security-alarm setting. As
another example, a first device can detect a user approaching a
front door (e.g., by detecting motion or sudden light pattern
changes). The first device may, e.g., cause a general audio or
visual signal to be presented (e.g., such as sounding of a
doorbell) or cause a location-specific audio or visual signal to be
presented (e.g., to announce the visitor's presence within a room
that a user is occupying).
[0041] In addition to detecting various types of events, the device
10 may include a light source 26 that may illuminate when a living
being, such as a human, is detected as approaching. The light
source 26 may include any type of light source such as one or more
light-emitting diodes or the like. The light source 26 may be
communicatively coupled to the high-power processor 20 and the
low-power processor 22, which may provide a signal to cause the
light source 26 to illuminate.
[0042] Keeping the foregoing in mind, FIG. 2 illustrates an example
of a smart-home environment 30 within which one or more of the
devices 10 of FIG. 1, methods, systems, services, and/or computer
program products described further herein can be applicable. The
depicted smart-home environment 30 includes a structure 32, which
can include, e.g., a house, office building, garage, or mobile
home. It will be appreciated that devices can also be integrated
into a smart-home environment 30 that does not include an entire
structure 32, such as an apartment, condominium, or office space.
Further, the smart home environment can control and/or be coupled
to devices outside of the actual structure 32. Indeed, several
devices in the smart home environment need not physically be within
the structure 32 at all. For example, a device controlling a pool
heater or irrigation system can be located outside of the structure
32.
[0043] The depicted structure 32 includes a plurality of rooms 38,
separated at least partly from each other via walls 40. The walls
40 can include interior walls or exterior walls. Each room can
further include a floor 42 and a ceiling 44. Devices can be mounted
on, integrated with and/or supported by a wall 40, floor 42 or
ceiling 44.
[0044] In some embodiments, the smart-home environment 30 of FIG. 2
includes a plurality of devices 10, including intelligent,
multi-sensing, network-connected devices, that can integrate
seamlessly with each other and/or with a central server or a
cloud-computing system to provide any of a variety of useful
smart-home objectives. The smart-home environment 30 may include
one or more intelligent, multi-sensing, network-connected
thermostats 46 (hereinafter referred to as "smart thermostats 46"),
one or more intelligent, network-connected, multi-sensing hazard
detection units 50 (hereinafter referred to as "smart hazard
detectors 50"), and one or more intelligent, multi-sensing,
network-connected entryway interface devices 52 (hereinafter
referred to as "smart doorbells 52"). According to embodiments, the
smart thermostat 46 may include a Nest.RTM. Learning
Thermostat--1st Generation T100577 or Nest.RTM. Learning
Thermostat--2nd Generation T200577 by Nest Labs, Inc., among
others. The smart thermostat 46 detects ambient climate
characteristics (e.g., temperature and/or humidity) and controls a
HVAC system 48 accordingly.
[0045] The smart hazard detector 50 may detect the presence of a
hazardous substance or a substance indicative of a hazardous
substance (e.g., smoke, fire, or carbon monoxide). The smart hazard
detector 50 may include a Nest.RTM. Protect that may include
sensors 12 such as smoke sensors, carbon monoxide sensors, and the
like. As such, the hazard detector 50 may determine when smoke,
fire, or carbon monoxide may be present within the building.
[0046] The smart doorbell 52 may detect a person's approach to or
departure from a location (e.g., an outer door), control doorbell
functionality, announce a person's approach or departure via audio
or visual means, or control settings on a security system (e.g., to
activate or deactivate the security system when occupants go and
come). The smart doorbell 52 may interact with other devices 10
based on whether someone has approached or entered the smart-home
environment 30.
[0047] In some embodiments, the smart-home environment 30 further
includes one or more intelligent, multi-sensing, network-connected
wall switches 54 (hereinafter referred to as "smart wall switches
54"), along with one or more intelligent, multi-sensing,
network-connected wall plug interfaces 56 (hereinafter referred to
as "smart wall plugs 56"). The smart wall switches 54 may detect
ambient lighting conditions, detect room-occupancy states, and
control a power and/or dim state of one or more lights. In some
instances, smart wall switches 54 may also control a power state or
speed of a fan, such as a ceiling fan. The smart wall plugs 56 may
detect occupancy of a room or enclosure and control supply of power
to one or more wall plugs (e.g., such that power is not supplied to
the plug if nobody is at home).
[0048] Still further, in some embodiments, the device 10 within the
smart-home environment 30 may further includes a plurality of
intelligent, multi-sensing, network-connected appliances 58
(hereinafter referred to as "smart appliances 58"), such as
refrigerators, stoves and/or ovens, televisions, washers, dryers,
lights, stereos, intercom systems, garage-door openers, floor fans,
ceiling fans, wall air conditioners, pool heaters, irrigation
systems, security systems, and so forth. According to embodiments,
the network-connected appliances 58 are made compatible with the
smart-home environment by cooperating with the respective
manufacturers of the appliances. For example, the appliances can be
space heaters, window AC units, motorized duct vents, etc. When
plugged in, an appliance can announce itself to the smart-home
network, such as by indicating what type of appliance it is, and it
can automatically integrate with the controls of the smart-home.
Such communication by the appliance to the smart home can be
facilitated by any wired or wireless communication protocols known
by those having ordinary skill in the art. The smart home also can
include a variety of non-communicating legacy appliances 68, such
as old conventional washer/dryers, refrigerators, and the like
which can be controlled, albeit coarsely (ON/OFF), by virtue of the
smart wall plugs 56. The smart-home environment 30 can further
include a variety of partially communicating legacy appliances 70,
such as infrared ("IR") controlled wall air conditioners or other
IR-controlled devices, which can be controlled by IR signals
provided by the smart hazard detectors 50 or the smart wall
switches 54.
[0049] According to embodiments, the smart thermostats 46, the
smart hazard detectors 50, the smart doorbells 52, the smart wall
switches 54, the smart wall plugs 56, and other devices of the
smart-home environment 30 are modular and can be incorporated into
older and new houses. For example, the devices 10 are designed
around a modular platform consisting of two basic components: a
head unit and a back plate, which is also referred to as a docking
station. Multiple configurations of the docking station are
provided so as to be compatible with any home, such as older and
newer homes. However, all of the docking stations include a
standard head-connection arrangement, such that any head unit can
be removably attached to any docking station. Thus, in some
embodiments, the docking stations are interfaces that serve as
physical connections to the structure and the voltage wiring of the
homes, and the interchangeable head units contain all of the
sensors 12, processors 28, user interfaces 14, the power supply 16,
the network interface 18, and other functional components of the
devices described above.
[0050] Many different commercial and functional possibilities for
provisioning, maintenance, and upgrade are possible. For example,
after years of using any particular head unit, a user will be able
to buy a new version of the head unit and simply plug it into the
old docking station. There are also many different versions for the
head units, such as low-cost versions with few features, and then a
progression of increasingly capable versions, up to and including
extremely fancy head units with a large number of features. Thus,
it should be appreciated that the various versions of the head
units can all be interchangeable, with any of them working when
placed into any docking station. This can advantageously encourage
sharing and re-deployment of old head units--for example, when an
important high-capability head unit, such as a hazard detector, is
replaced by a new version of the head unit, then the old head unit
can be re-deployed to a back room or basement, etc. According to
embodiments, when first plugged into a docking station, the head
unit can ask the user (by 2D LCD display, 2D/3D holographic
projection, voice interaction, etc.) a few simple questions such
as, "Where am I" and the user can indicate "living room", "kitchen"
and so forth.
[0051] The smart-home environment 30 may also include communication
with devices outside of the physical home but within a proximate
geographical range of the home. For example, the smart-home
environment 30 may include a pool heater monitor 34 that
communicates a current pool temperature to other devices within the
smart-home environment 30 or receives commands for controlling the
pool temperature. Similarly, the smart-home environment 30 may
include an irrigation monitor 36 that communicates information
regarding irrigation systems within the smart-home environment 30
and/or receives control information for controlling such irrigation
systems. According to embodiments, an algorithm is provided for
considering the geographic location of the smart-home environment
30, such as based on the zip code or geographic coordinates of the
home. The geographic information is then used to obtain data
helpful for determining optimal times for watering, such data may
include sun location information, temperature, dew point, soil type
of the land on which the home is located, etc.
[0052] By virtue of network connectivity, one or more of the
smart-home devices of FIG. 2 can further allow a user to interact
with the device even if the user is not proximate to the device.
For example, a user can communicate with a device using a computer
(e.g., a desktop computer, laptop computer, or tablet) or other
portable electronic device (e.g., a smartphone) 66. A web page or
app can be configured to receive communications from the user and
control the device based on the communications and/or to present
information about the device's operation to the user. For example,
the user can view a current set point temperature for a device and
adjust it using a computer. The user can be in the structure during
this remote communication or outside the structure.
[0053] As discussed, users can control the smart thermostat and
other smart devices in the smart-home environment 30 using a
network-connected computer or portable electronic device 66. In
some examples, some or all of the occupants (e.g., individuals who
live in the home) can register their device 66 with the smart-home
environment 30. Such registration can be made at a central server
to authenticate the occupant and/or the device as being associated
with the home and to give permission to the occupant to use the
device to control the smart devices in the home. An occupant can
use their registered device 66 to remotely control the smart
devices of the home, such as when the occupant is at work or on
vacation. The occupant may also use their registered device to
control the smart devices when the occupant is actually located
inside the home, such as when the occupant is sitting on a couch
inside the home. It should be appreciated that instead of or in
addition to registering devices 66, the smart-home environment 30
makes inferences about which individuals live in the home and are
therefore occupants and which devices 66 are associated with those
individuals. As such, the smart-home environment "learns" who is an
occupant and permits the devices 66 associated with those
individuals to control the smart devices of the home.
[0054] In some instances, guests desire to control the smart
devices. For example, the smart-home environment may receive
communication from an unregistered mobile device of an individual
inside of the home, where said individual is not recognized as an
occupant of the home. Further, for example, a smart-home
environment may receive communication from a mobile device of an
individual who is known to be or who is registered as a guest.
[0055] According to embodiments, a guest-layer of controls can be
provided to guests of the smart-home environment 30. The
guest-layer of controls gives guests access to basic controls
(e.g., a judicially selected subset of features of the smart
devices), such as temperature adjustments, but it locks out other
functionalities. The guest layer of controls can be thought of as a
"safe sandbox" in which guests have limited controls, but they do
not have access to more advanced controls that could fundamentally
alter, undermine, damage, or otherwise impair the occupant-desired
operation of the smart devices. For example, the guest layer of
controls will not permit the guest to adjust the heat-pump lockout
temperature.
[0056] A use case example of this is when a guest is in a smart
home, the guest could walk up to the thermostat and turn the dial
manually, but the guest may not want to walk around the house
"hunting" the thermostat, especially at night while the home is
dark and others are sleeping. Further, the guest may not want to go
through the hassle of downloading the necessary application to
their device for remotely controlling the thermostat. In fact, the
guest may not have the homeowner's login credentials, etc., and
therefore cannot remotely control the thermostat via such an
application. Accordingly, according to embodiments of the
invention, the guest can open a mobile browser on their mobile
device, type a keyword, such as "NEST" into the URL field and tap
"Go" or "Search", etc. In response, the device presents the guest
with a user interface, which allows the guest to move the target
temperature between a limited range, such as 65 and 80 degrees
Fahrenheit. As discussed, the user interface provides a guest layer
of controls that are limited to basic functions. The guest cannot
change the target humidity, modes, or view energy history.
[0057] According to embodiments, to enable guests to access the
user interface that provides the guest layer of controls, a local
webserver is provided that is accessible in the local area network
(LAN). It does not require a password, because physical presence
inside the home is established reliably enough by the guest's
presence on the LAN. In some embodiments, during installation of
the smart device, such as the smart thermostat, the homeowner is
asked if they want to enable a Local Web App (LWA) on the smart
device. Business owners will likely say no; homeowners will likely
say yes. When the LWA option is selected, the smart device
broadcasts to the LAN that the above referenced keyword, such as
"NEST", is now a host alias for its local web server. Thus, no
matter whose home a guest goes to, that same keyword (e.g., "NEST")
is always the URL you use to access the LWA, provided the smart
device is purchased from the same manufacturer. Further, according
to embodiments, if there is more than one smart device on the LAN,
the second and subsequent smart devices do not offer to set up
another LWA. Instead, they register themselves as target candidates
with the master LWA. And in this case the LWA user would be asked
which smart device they want to change the temperature on before
getting the simplified user interface for the particular smart
device they choose.
[0058] According to embodiments, a guest layer of controls may also
be provided to users by means other than a device 66. For example,
the smart device, such as the smart thermostat, may be equipped
with walkup-identification technology (e.g., face recognition,
RFID, ultrasonic sensors) that "fingerprints" or creates a
"signature" for the occupants of the home. The
walkup-identification technology can be the same as or similar to
the fingerprinting and signature creating techniques described in
other sections of this application. In operation, when a person who
does not live in the home or is otherwise not registered with the
smart home or whose fingerprint or signature is not recognized by
the smart home "walks up" to a smart device, the smart device
provides the guest with the guest layer of controls, rather than
full controls.
[0059] As described below, the smart thermostat 46 and other smart
devices "learn" by observing occupant behavior. For example, the
smart thermostat learns occupants' preferred temperature set-points
for mornings and evenings, and it learns when the occupants are
asleep or awake, as well as when the occupants are typically away
or at home, for example. According to embodiments, when a guest
controls the smart devices, such as the smart thermostat, the smart
devices do not "learn" from the guest. This prevents the guest's
adjustments and controls from affecting the learned preferences of
the occupants.
[0060] According to some embodiments, a smart television remote
control is provided. The smart remote control recognizes occupants
by thumbprint, visual identification, RFID, etc., and it recognizes
a user as a guest or as someone belonging to a particular class
having limited control and access (e.g., child). Upon recognizing
the user as a guest or someone belonging to a limited class, the
smart remote control only permits that user to view a subset of
channels and to make limited adjustments to the settings of the
television and other devices. For example, a guest cannot adjust
the digital video recorder (DVR) settings, and a child is limited
to viewing child-appropriate programming.
[0061] According to some embodiments, similar controls are provided
for other instruments, utilities, and devices in the house. For
example, sinks, bathtubs, and showers can be controlled by smart
spigots that recognize users as guests or as children and therefore
prevent water from exceeding a designated temperature that is
considered safe.
[0062] In some embodiments, in addition to containing processing
and sensing capabilities, each of the devices 34, 36, 46, 50, 52,
54, 56, and 58 (collectively referred to as "the smart devices") is
capable of data communications and information sharing with any
other of the smart devices, as well as to any central server or
cloud-computing system or any other device that is
network-connected anywhere in the world. The required data
communications can be carried out using any of a variety of custom
or standard wireless protocols (Wi-Fi, ZigBee, 6LoWPAN, etc.)
and/or any of a variety of custom or standard wired protocols (CAT6
Ethernet, HomePlug, etc.).
[0063] According to embodiments, all or some of the smart devices
can serve as wireless or wired repeaters. For example, a first one
of the smart devices can communicate with a second one of the smart
device via a wireless router 60. The smart devices can further
communicate with each other via a connection to a network, such as
the Internet 62. Through the Internet 62, the smart devices can
communicate with a central server or a cloud-computing system 64.
The central server or cloud-computing system 64 can be associated
with a manufacturer, support entity, or service provider associated
with the device. For one embodiment, a user may be able to contact
customer support using a device itself rather than needing to use
other communication means such as a telephone or Internet-connected
computer. Further, software updates can be automatically sent from
the central server or cloud-computing system 64 to devices (e.g.,
when available, when purchased, or at routine intervals). In
certain embodiments, the cloud-computing system 64 may receive data
from each of the devices within the smart-home environment 30, such
that the data regarding the smart-home environment 60 may be stored
remotely, analyzed, shared with certain service providers, and the
like.
[0064] According to embodiments, the smart devices combine to
create a mesh network of spokesman and low-power nodes in the
smart-home environment 30, where some of the smart devices are
"spokesman" nodes and others are "low-powered" nodes. Some of the
smart devices in the smart-home environment 30 are battery powered,
while others have a regular and reliable power source, such as by
connecting to wiring (e.g., to 120V line voltage wires) behind the
walls 40 of the smart-home environment. The smart devices that have
a regular and reliable power source are referred to as "spokesman"
nodes. These nodes are equipped with the capability of using any
wireless protocol or manner to facilitate bidirectional
communication with any of a variety of other devices in the
smart-home environment 30 as well as with the central server or
cloud-computing system 64. On the other hand, the devices that are
battery powered are referred to as "low-power" nodes. These nodes
tend to be smaller than spokesman nodes and can only communicate
using wireless protocols that require very little power, such as
Zigbee, 6LoWPAN, etc. Further, some, but not all, low-power nodes
are incapable of bidirectional communication. These low-power nodes
send messages, but they are unable to "listen". Thus, other devices
in the smart-home environment 30, such as the spokesman nodes,
cannot send information to these low-power nodes.
[0065] As described, the smart devices serve as low power and
spokesman nodes to create a mesh network in the smart-home
environment 30. Individual low-power nodes in the smart-home
environment regularly send out messages regarding what they are
sensing, and the other low-powered nodes in the smart-home
environment--in addition to sending out their own messages--repeat
the messages, thereby causing the messages to travel from node to
node (i.e., device to device) throughout the smart-home environment
30. The spokesman nodes in the smart-home environment 30 are able
to "drop down" to low-powered communication protocols to receive
these messages, translate the messages to other communication
protocols, and send the translated messages to other spokesman
nodes and/or the central server or cloud-computing system 64. Thus,
the low-powered nodes using low-power communication protocols are
able send messages across the entire smart-home environment 30 as
well as over the Internet 62 to the central server or
cloud-computing system 64. According to embodiments, the mesh
network enables the central server or cloud-computing system 64 to
regularly receive data from all of the smart devices in the home,
make inferences based on the data, and send commands back to one of
the smart devices to accomplish some of the smart-home objectives
described herein.
[0066] As described, the spokesman nodes and some of the
low-powered nodes are capable of "listening". Accordingly, users,
other devices, and the central server or cloud-computing system 64
can communicate controls to the low-powered nodes. For example, a
user can use the portable electronic device (e.g., a smartphone) 66
to send commands over the Internet 62 to the central server or
cloud-computing system 64, which then relays the commands to the
spokesman nodes in the smart-home environment 30. The spokesman
nodes drop down to a low-power protocol to communicate the commands
to the low-power nodes throughout the smart-home environment, as
well as to other spokesman nodes that did not receive the commands
directly from the central server or cloud-computing system 64.
[0067] An example of a low-power node is a smart night-light 65. In
addition to housing a light source, the smart night light 65 houses
an occupancy sensor, such as an ultrasonic or passive IR sensor,
and an ambient light sensor, such as a photoresistor or a
single-pixel sensor that measures light in the room. In some
embodiments, the smart night-light 65 is configured to activate the
light source when its ambient light sensor detects that the room is
dark and when its occupancy sensor detects that someone is in the
room. In other embodiments, the smart night-light 65 is simply
configured to activate the light source when its ambient light
sensor detects that the room is dark. Further, according to
embodiments, the smart night light 65 includes a low-power wireless
communication chip (e.g., ZigBee chip) that regularly sends out
messages regarding the occupancy of the room and the amount of
light in the room, including instantaneous messages coincident with
the occupancy sensor detecting the presence of a person in the
room. As mentioned above, these messages may be sent wirelessly,
using the mesh network, from node to node (i.e., smart device to
smart device) within the smart-home environment 30 as well as over
the Internet 62 to the central server or cloud-computing system
64.
[0068] Other examples of low-powered nodes include battery-operated
versions of the smart hazard detectors 50. These smart hazard
detectors 50 are often located in an area without access to
constant and reliable power and, as discussed in detail below, may
include any number and type of sensors, such as smoke/fire/heat
sensors, carbon monoxide/dioxide sensors, occupancy/motion sensors,
ambient light sensors, temperature sensors, humidity sensors, and
the like. Furthermore, smart hazard detectors 50 can send messages
that correspond to each of the respective sensors to the other
devices and the central server or cloud-computing system 64, such
as by using the mesh network as described above.
[0069] Examples of spokesman nodes include smart thermostats 46,
smart doorbells 52, smart wall switches 54, and smart wall plugs
56. These devices 46, 52, 54, and 56 are often located near and
connected to a reliable power source, and therefore can include
more power-consuming components, such as one or more communication
chips capable of bidirectional communication in any variety of
protocols.
[0070] In some embodiments, these low-powered and spokesman nodes
(e.g., devices 46, 50, 52, 54, 56, 58, and 65) can function as
"tripwires" for an alarm system in the smart-home environment. For
example, in the event a perpetrator circumvents detection by alarm
sensors located at windows, doors, and other entry points of the
smart-home environment 30, the alarm could be triggered upon
receiving an occupancy, motion, heat, sound, etc. message from one
or more of the low-powered and spokesman nodes in the mesh network.
For example, upon receiving a message from a smart night light 65
indicating the presence of a person, the central server or
cloud-computing system 64 or some other device could trigger an
alarm, provided the alarm is armed at the time of detection. Thus,
the alarm system could be enhanced by various low-powered and
spokesman nodes located throughout the smart-home environment 30.
In this example, a user could enhance the security of the
smart-home environment 30 by buying and installing extra smart
nightlights 65. However, in a scenario where the perpetrator uses a
radio transceiver to jam the wireless network, the devices 10 may
be incapable of communicating with each other. Therefore, as
discussed in detail below, the present techniques provide network
communication jamming attack detection and notification solutions
to such a problem.
[0071] In some embodiments, the mesh network can be used to
automatically turn on and off lights as a person transitions from
room to room. For example, the low-powered and spokesman nodes
detect the person's movement through the smart-home environment and
communicate corresponding messages through the mesh network. Using
the messages that indicate which rooms are occupied, the central
server or cloud-computing system 64 or some other device activates
and deactivates the smart wall switches 54 to automatically provide
light as the person moves from room to room in the smart-home
environment 30. Further, users may provide pre-configuration
information that indicates which smart wall plugs 56 provide power
to lamps and other light sources, such as the smart night-light 65.
Alternatively, this mapping of light sources to wall plugs 56 can
be done automatically (e.g., the smart wall plugs 56 detect when a
light source is plugged into it, and it sends a corresponding
message to the central server or cloud-computing system 64). Using
this mapping information in combination with messages that indicate
which rooms are occupied, the central server or cloud-computing
system 64 or some other device activates and deactivates the smart
wall plugs 56 that provide power to lamps and other light sources
so as to track the person's movement and provide light as the
person moves from room to room.
[0072] In some embodiments, the mesh network of low-powered and
spokesman nodes can be used to provide exit lighting in the event
of an emergency. In some instances, to facilitate this, users
provide pre-configuration information that indicates exit routes in
the smart-home environment 30. For example, for each room in the
house, the user provides a map of the best exit route. It should be
appreciated that instead of a user providing this information, the
central server or cloud-computing system 64 or some other device
could automatically determine the routes using uploaded maps,
diagrams, architectural drawings of the smart-home house, as well
as using a map generated based on positional information obtained
from the nodes of the mesh network (e.g., positional information
from the devices is used to construct a map of the house). In
operation, when an alarm is activated (e.g., when one or more of
the smart hazard detector 50 detects smoke and activates an alarm),
the central server or cloud-computing system 64 or some other
device uses occupancy information obtained from the low-powered and
spokesman nodes to determine which rooms are occupied and then
turns on lights (e.g., nightlights 65, wall switches 54, wall plugs
56 that power lamps, etc.) along the exit routes from the occupied
rooms so as to provide emergency exit lighting.
[0073] Further included and illustrated in the smart-home
environment 30 of FIG. 2 are service robots 69 each configured to
carry out, in an autonomous manner, any of a variety of household
tasks. For some embodiments, the service robots 69 can be
respectively configured to perform floor sweeping, floor washing,
etc. in a manner similar to that of known commercially available
devices such as the ROOMBA.TM. and SCOOBA.TM. products sold by
iRobot, Inc. of Bedford, Mass. Tasks such as floor sweeping and
floor washing can be considered as "away" or "while-away" tasks for
purposes of the instant description, as it is generally more
desirable for these tasks to be performed when the occupants are
not present. For other embodiments, one or more of the service
robots 69 are configured to perform tasks such as playing music for
an occupant, serving as a localized thermostat for an occupant,
serving as a localized air monitor/purifier for an occupant,
serving as a localized baby monitor, serving as a localized hazard
detector for an occupant, and so forth, it being generally more
desirable for such tasks to be carried out in the immediate
presence of the human occupant. For purposes of the instant
description, such tasks can be considered as "human-facing" or
"human-centric" tasks.
[0074] When serving as a localized thermostat for an occupant, a
particular one of the service robots 69 can be considered to be
facilitating what can be called a "personal comfort-area network"
for the occupant, with the objective being to keep the occupant's
immediate space at a comfortable temperature wherever that occupant
may be located in the home. This can be contrasted with
conventional wall-mounted room thermostats, which have the more
attenuated objective of keeping a statically-defined structural
space at a comfortable temperature. According to one embodiment,
the localized-thermostat service robot 69 is configured to move
itself into the immediate presence (e.g., within five feet) of a
particular occupant who has settled into a particular location in
the home (e.g. in the dining room to eat their breakfast and read
the news). The localized-thermostat service robot 69 includes a
temperature sensor, a processor, and wireless communication
components configured such that control communications with the
HVAC system, either directly or through a wall-mounted wirelessly
communicating thermostat coupled to the HVAC system, are maintained
and such that the temperature in the immediate vicinity of the
occupant is maintained at their desired level. If the occupant then
moves and settles into another location (e.g. to the living room
couch to watch television), the localized-thermostat service robot
69 proceeds to move and park itself next to the couch and keep that
particular immediate space at a comfortable temperature.
[0075] Technologies by which the localized-thermostat service robot
69 (and/or the larger smart-home system of FIG. 2) can identify and
locate the occupant whose personal-area space is to be kept at a
comfortable temperature can include, but are not limited to, RFID
sensing (e.g., person having an RFID bracelet, RFID necklace, or
RFID key fob), synthetic vision techniques (e.g., video cameras and
face recognition processors), audio techniques (e.g., voice, sound
pattern, vibration pattern recognition), ultrasound sensing/imaging
techniques, and infrared or near-field communication (NFC)
techniques (e.g., person wearing an infrared or NFC-capable
smartphone), along with rules-based inference engines or artificial
intelligence techniques that draw useful conclusions from the
sensed information (e.g., if there is only a single occupant
present in the home, then that is the person whose immediate space
should be kept at a comfortable temperature, and the selection of
the desired comfortable temperature should correspond to that
occupant's particular stored profile).
[0076] When serving as a localized air monitor/purifier for an
occupant, a particular service robot 69 can be considered to be
facilitating what can be called a "personal health-area network"
for the occupant, with the objective being to keep the air quality
in the occupant's immediate space at healthy levels. Alternatively
or in conjunction therewith, other health-related functions can be
provided, such as monitoring the temperature or heart rate of the
occupant (e.g., using finely remote sensors, near-field
communication with on-person monitors, etc.). When serving as a
localized hazard detector for an occupant, a particular service
robot 69 can be considered to be facilitating what can be called a
"personal safety-area network" for the occupant, with the objective
being to ensure there is no excessive carbon monoxide, smoke, fire,
etc., in the immediate space of the occupant. Methods analogous to
those described above for personal comfort-area networks in terms
of occupant identifying and tracking are likewise applicable for
personal health-area network and personal safety-area network
embodiments.
[0077] According to some embodiments, the above-referenced
facilitation of personal comfort-area networks, personal
health-area networks, personal safety-area networks, and/or other
such human-facing functionalities of the service robots 69, are
further enhanced by logical integration with other smart sensors in
the home according to rules-based inferencing techniques or
artificial intelligence techniques for achieving better performance
of those human-facing functionalities and/or for achieving those
goals in energy-conserving or other resource-conserving ways. Thus,
for one embodiment relating to personal health-area networks, the
air monitor/purifier service robot 69 can be configured to detect
whether a household pet is moving toward the currently settled
location of the occupant (e.g., using on-board sensors and/or by
data communications with other smart-home sensors along with
rules-based inferencing/artificial intelligence techniques), and if
so, the air purifying rate is immediately increased in preparation
for the arrival of more airborne pet dander. For another embodiment
relating to personal safety-area networks, the hazard detector
service robot 69 can be advised by other smart-home sensors that
the temperature and humidity levels are rising in the kitchen,
which is nearby to the occupant's current dining room location, and
responsive to this advisory the hazard detector service robot 69
will temporarily raise a hazard detection threshold, such as a
smoke detection threshold, under an inference that any small
increases in ambient smoke levels will most likely be due to
cooking activity and not due to a genuinely hazardous
condition.
[0078] The above-described "human-facing" and "away"
functionalities can be provided, without limitation, by multiple
distinct service robots 69 having respective dedicated ones of such
functionalities, by a single service robot 69 having an integration
of two or more different ones of such functionalities, and/or any
combinations thereof (including the ability for a single service
robot 69 to have both "away" and "human facing" functionalities)
without departing from the scope of the present teachings.
Electrical power can be provided by virtue of rechargeable
batteries or other rechargeable methods, such as an out-of-the-way
docking station to which the service robots 69 will automatically
dock and recharge its batteries (if needed) during periods of
inactivity. Preferably, each service robot 69 includes wireless
communication components that facilitate data communications with
one or more of the other wirelessly communicating smart-home
sensors of FIG. 2 and/or with one or more other service robots 69
(e.g., using Wi-Fi, Zigbee, Z-Wave, 6LoWPAN, etc.), and one or more
of the smart-home devices 10 can be in communication with a remote
server over the Internet. Alternatively or in conjunction
therewith, each service robot 69 can be configured to communicate
directly with a remote server by virtue of cellular telephone
communications, satellite communications, 3G/4G network data
communications, or other direct communication method.
[0079] Provided according to some embodiments are systems and
methods relating to the integration of the service robot(s) 69 with
home security sensors and related functionalities of the smart home
system. The embodiments are particularly applicable and
advantageous when applied for those service robots 69 that perform
"away" functionalities or that otherwise are desirable to be active
when the home is unoccupied (hereinafter "away-service robots").
Included in the embodiments are methods and systems for ensuring
that home security systems, intrusion detection systems, and/or
occupancy-sensitive environmental control systems (for example,
occupancy-sensitive automated setback thermostats that enter into a
lower-energy-using condition when the home is unoccupied) are not
erroneously triggered by the away-service robots.
[0080] Provided according to one embodiment is a home automation
and security system (e.g., as shown in FIG. 2) that is remotely
monitored by a monitoring service by virtue of automated systems
(e.g., cloud-based servers or other central servers, hereinafter
"central server") that are in data communications with one or more
network-connected elements of the home automation and security
system. The away-service robots are configured to be in operative
data communication with the central server, and are configured such
that they remain in a non-away-service state (e.g., a dormant state
at their docking station) unless permission is granted from the
central server (e.g., by virtue of an "away-service-OK" message
from the central server) to commence their away-service activities.
An away-state determination made by the system, which can be
arrived at (i) exclusively by local on-premises smart device(s)
based on occupancy sensor data, (ii) exclusively by the central
server based on received occupancy sensor data and/or based on
received proximity-related information such as GPS coordinates from
user smartphones or automobiles, or (iii) any combination of (i)
and (ii) can then trigger the granting of away-service permission
to the away-service robots by the central server. During the course
of the away-service robot activity, during which the away-service
robots may continuously detect and send their in-home location
coordinates to the central server, the central server can readily
filter signals from the occupancy sensing devices to distinguish
between the away-service robot activity versus any unexpected
intrusion activity, thereby avoiding a false intrusion alarm
condition while also ensuring that the home is secure.
Alternatively or in conjunction therewith, the central server may
provide filtering data (such as an expected occupancy-sensing
profile triggered by the away-service robots) to the occupancy
sensing nodes or associated processing nodes of the smart home,
such that the filtering is performed at the local level. Although
somewhat less secure, it would also be within the scope of the
present teachings for the central server to temporarily disable the
occupancy sensing equipment for the duration of the away-service
robot activity.
[0081] According to another embodiment, functionality similar to
that of the central server in the above example can be performed by
an on-site computing device such as a dedicated server computer, a
"master" home automation console or panel, or as an adjunct
function of one or more of the smart-home devices of FIG. 2. In
such an embodiment, there would be no dependency on a remote
service provider to provide the "away-service-OK" permission to the
away-service robots and the false-alarm-avoidance filtering service
or filter information for the sensed intrusion detection
signals.
[0082] According to other embodiments, there are provided methods
and systems for implementing away-service robot functionality while
avoiding false home security alarms and false occupancy-sensitive
environmental controls without the requirement of a single overall
event orchestrator. For purposes of the simplicity in the present
disclosure, the home security systems and/or occupancy-sensitive
environmental controls that would be triggered by the motion,
noise, vibrations, or other disturbances of the away-service robot
activity are referenced simply as "activity sensing systems," and
when so triggered will yield a "disturbance-detected" outcome
representative of the false trigger (for example, an alarm message
to a security service, or an "arrival" determination for an
automated setback thermostat that causes the home to be heated or
cooled to a more comfortable "occupied" set point temperature).
According to one embodiment, the away-service robots are configured
to emit a standard ultrasonic sound throughout the course of their
away-service activity, the activity sensing systems are configured
to detect that standard ultrasonic sound, and the activity sensing
systems are further configured such that no disturbance-detected
outcome will occur for as long as that standard ultrasonic sound is
detected. For other embodiments, the away-service robots are
configured to emit a standard notification signal throughout the
course of their away-service activity, the activity sensing systems
are configured to detect that standard notification signal, and the
activity sensing systems are further configured such that no
disturbance-detected outcome will occur for as long as that
standard notification signal is detected, wherein the standard
notification signal comprises one or more of: an optical notifying
signal; an audible notifying signal; an infrared notifying signal;
an infrasonic notifying signal; a wirelessly transmitted data
notification signal (e.g., an IP broadcast, multicast, or unicast
notification signal, or a notification message sent in an TCP/IP
two-way communication session).
[0083] According to some embodiments, the notification signals sent
by the away-service robots to the activity sensing systems are
authenticated and encrypted such that the notifications cannot be
learned and replicated by a potential burglar. Any of a variety of
known encryption/authentication schemes can be used to ensure such
data security including, but not limited to, methods involving
third party data security services or certificate authorities. For
some embodiments, a permission request-response model can be used,
wherein any particular away-service robot requests permission from
each activity sensing system in the home when it is ready to
perform its away-service tasks, and does not initiate such activity
until receiving a "yes" or "permission granted" message from each
activity sensing system (or from a single activity sensing system
serving as a "spokesman" for all of the activity sensing systems).
One advantage of the described embodiments that do not require a
central event orchestrator is that there can (optionally) be more
of an arms-length relationship between the supplier(s) of the home
security/environmental control equipment, on the one hand, and the
supplier(s) of the away-service robot(s), on the other hand, as it
is only required that there is the described standard one-way
notification protocol or the described standard two-way
request/permission protocol to be agreed upon by the respective
suppliers.
[0084] According to still other embodiments, the activity sensing
systems are configured to detect sounds, vibrations, RF emissions,
or other detectable environmental signals or "signatures" that are
intrinsically associated with the away-service activity of each
away-service robot, and are further configured such that no
disturbance-detected outcome will occur for as long as that
particular detectable signal or environmental "signature" is
detected. By way of example, a particular kind of vacuum-cleaning
away-service robot may emit a specific sound or RF signature. For
one embodiment, the away-service environmental signatures for each
of a plurality of known away-service robots are stored in the
memory of the activity sensing systems based on empirically
collected data, the environmental signatures being supplied with
the activity sensing systems and periodically updated by a remote
update server. For another embodiment, the activity sensing systems
can be placed into a "training mode" for the particular home in
which they are installed, wherein they "listen" and "learn" the
particular environmental signatures of the away-service robots for
that home during that training session, and thereafter will
suppress disturbance-detected outcomes for intervals in which those
environmental signatures are heard.
[0085] For still another embodiment, which is particularly useful
when the activity sensing system is associated with
occupancy-sensitive environmental control equipment rather than a
home security system, the activity sensing system is configured to
automatically learn the environmental signatures for the
away-service robots by virtue of automatically performing
correlations over time between detected environmental signatures
and detected occupancy activity. By way of example, for one
embodiment an intelligent automated nonoccupancy-triggered setback
thermostat such as the Nest Learning Thermostat can be configured
to constantly monitor for audible and RF activity as well as to
perform infrared-based occupancy detection. In particular view of
the fact that the environmental signature of the away-service robot
will remain relatively constant from event to event, and in view of
the fact that the away-service events will likely either (a)
themselves be triggered by some sort of nonoccupancy condition as
measured by the away-service robots themselves, or (b) occur at
regular times of day, there will be patterns in the collected data
by which the events themselves will become apparent and for which
the environmental signatures can be readily learned. Generally
speaking, for this automatic-learning embodiment in which the
environmental signatures of the away-service robots are
automatically learned without requiring user interaction, it is
more preferable that a certain number of false triggers be
tolerable over the course of the learning process. Accordingly,
this automatic-learning embodiment is more preferable for
application in occupancy-sensitive environmental control equipment
(such as an automated setback thermostat) rather than home security
systems for the reason that a few false occupancy determinations
may cause a few instances of unnecessary heating or cooling, but
will not otherwise have any serious consequences, whereas false
home security alarms may have more serious consequences.
[0086] According to embodiments, technologies including the sensors
of the smart devices located in the mesh network of the smart-home
environment in combination with rules-based inference engines or
artificial intelligence provided at the central server or
cloud-computing system 64 are used to provide a personal "smart
alarm clock" for individual occupants of the home. For example,
user-occupants can communicate with the central server or
cloud-computing system 64 via their mobile devices 66 to access an
interface for the smart alarm clock. There, occupants can turn on
their "smart alarm clock" and input a wake time for the next day
and/or for additional days. In some embodiments, the occupant may
have the option of setting a specific wake time for each day of the
week, as well as the option of setting some or all of the inputted
wake times to "repeat". Artificial intelligence will be used to
consider the occupant's response to these alarms when they go off
and make inferences about the user's preferred sleep patterns over
time.
[0087] According to embodiments, the smart device in the smart-home
environment 30 that happens to be closest to the occupant when the
occupant falls asleep will be the device that transmits messages
regarding when the occupant stopped moving, from which the central
server or cloud-computing system 64 will make inferences about
where and when the occupant prefers to sleep. This closest smart
device will be the device that sounds the alarm to wake the
occupant. In this manner, the "smart alarm clock" will follow the
occupant throughout the house, by tracking the individual occupants
based on their "unique signature", which is determined based on
data obtained from sensors located in the smart devices. For
example, the sensors include ultrasonic sensors, passive IR
sensors, and the like. The unique signature is based on a
combination of walking gate, patterns of movement, voice, height,
size, etc. It should be appreciated that facial recognition may
also be used.
[0088] According to an embodiment, the wake times associated with
the "smart alarm clock" are used by the smart thermostat 46 to
control the HVAC in an efficient manner so as to pre-heat or cool
the house to the occupant's desired "sleeping" and "awake"
temperature settings. The preferred settings can be learned over
time, such as by observing which temperature the occupant sets the
thermostat to before going to sleep and which temperature the
occupant sets the thermostat to upon waking up.
[0089] According to an embodiment, a device is positioned proximate
to the occupant's bed, such as on an adjacent nightstand, and
collects data as the occupant sleeps using noise sensors, motion
sensors (e.g., ultrasonic, IR, and optical), etc. Data may be
obtained by the other smart devices in the room as well. Such data
may include the occupant's breathing patterns, heart rate,
movement, etc. Inferences are made based on this data in
combination with data that indicates when the occupant actually
wakes up. For example, if--on a regular basis--the occupant's heart
rate, breathing, and moving all increase by 5% to 10%, twenty to
thirty minutes before the occupant wakes up each morning, then
predictions can be made regarding when the occupant is going to
wake. Other devices in the home can use these predictions to
provide other smart-home objectives, such as adjusting the smart
thermostat 46 so as to pre-heat or cool the home to the occupant's
desired setting before the occupant wakes up. Further, these
predictions can be used to set the "smart alarm clock" for the
occupant, to turn on lights, etc.
[0090] According to embodiments, technologies including the sensors
of the smart devices located throughout the smart-home environment
in combination with rules-based inference engines or artificial
intelligence provided at the central server or cloud-computing
system 64 are used to detect or monitor the progress of Alzheimer's
Disease. For example, the unique signatures of the occupants are
used to track the individual occupants' movement throughout the
smart-home environment 30. This data can be aggregated and analyzed
to identify patterns indicative of Alzheimer's. Oftentimes,
individuals with Alzheimer's have distinctive patterns of migration
in their homes. For example, a person will walk to the kitchen and
stand there for a while, then to the living room and stand there
for a while, and then back to the kitchen. This pattern will take
about thirty minutes, and then the person will repeat the pattern.
According to embodiments, the remote servers or cloud computing
architectures 64 analyze the person's migration data collected by
the mesh network of the smart-home environment to identify such
patterns.
[0091] In addition, FIG. 3 illustrates an embodiment of an
extensible devices and services platform 80 that can be
concentrated at a single server or distributed among several
different computing (e.g., cloud-computing system 64) entities
without limitation with respect to the smart-home environment 30.
The extensible devices and services platform 80 may include a
processing engine 86, which may include engines that receive data
from devices of smart-home environments (e.g., via the Internet or
a hubbed network), to index the data, to analyze the data and/or to
generate statistics based on the analysis or as part of the
analysis. The analyzed data can be stored as derived home data
88.
[0092] Results of the analysis or statistics can thereafter be
transmitted back to the device that provided home data used to
derive the results, to other devices, to a server providing a web
page to a user of the device, or to other non-device entities. For
example, use statistics, use statistics relative to use of other
devices, use patterns, and/or statistics summarizing sensor
readings can be generated by the processing engine 86 and
transmitted. The results or statistics can be provided via the
Internet 62. In this manner, the processing engine 86 can be
configured and programmed to derive a variety of useful information
from the home data 82. A single server can include one or more
engines.
[0093] The derived data can be highly beneficial at a variety of
different granularities for a variety of useful purposes, ranging
from explicit programmed control of the devices on a per-home,
per-neighborhood, or per-region basis (for example, demand-response
programs for electrical utilities), to the generation of
inferential abstractions that can assist on a per-home basis (for
example, an inference can be drawn that the homeowner has left for
vacation and so security detection equipment can be put on
heightened sensitivity), to the generation of statistics and
associated inferential abstractions that can be used for government
or charitable purposes. For example, processing engine 86 can
generate statistics about device usage across a population of
devices and send the statistics to device users, service providers
or other entities (e.g., that have requested or may have provided
monetary compensation for the statistics).
[0094] According to some embodiments, the home data 82, the derived
home data 88, and/or another data can be used to create "automated
neighborhood safety networks." For example, in the event the
central server or cloud-computing architecture 64 receives data
indicating that a particular home has been broken into, is
experiencing a fire, or some other type of emergency event, an
alarm is sent to other smart homes in the "neighborhood." In some
instances, the central server or cloud-computing architecture 64
automatically identifies smart homes within a radius of the home
experiencing the emergency and sends an alarm to the identified
homes. In such instances, the other homes in the "neighborhood" do
not have to sign up for or register to be a part of a safety
network, but instead are notified of an emergency based on their
proximity to the location of the emergency. This creates robust and
evolving neighborhood security watch networks, such that if one
person's home is getting broken into, an alarm can be sent to
nearby homes, such as by audio announcements via the smart devices
located in those homes. It should be appreciated that this can be
an opt-in service and that, in addition to or instead of the
central server or cloud-computing architecture 64 selecting which
homes to send alerts to, individuals can subscribe to participate
in such networks and individuals can specify which homes they want
to receive alerts from. This can include, for example, the homes of
family members who live in different cities, such that individuals
can receive alerts when their loved ones in other locations are
experiencing an emergency.
[0095] According to some embodiments, sound, vibration, and/or
motion sensing components of the smart devices are used to detect
sound, vibration, and/or motion created by running water. Based on
the detected sound, vibration, and/or motion, the central server or
cloud-computing system 64 makes inferences about water usage in the
home and provides related services. For example, the central server
or cloud-computing system 64 can run programs/algorithms that
recognize what water sounds like and when it is running in the
home. According to one embodiment, to map the various water sources
of the home, upon detecting running water, the central server or
cloud-computing system 64 sends a message an occupant's mobile
device asking if water is currently running or if water has been
recently run in the home and, if so, which room and which
water-consumption appliance (e.g., sink, shower, toilet, etc.) was
the source of the water. This enables the central server or
cloud-computing architecture 64 to determine the "signature" or
"fingerprint" of each water source in the home. This is sometimes
referred to herein as "audio fingerprinting water usage."
[0096] In one illustrative example, the central server or
cloud-computing architecture 64 creates a signature for the toilet
in the master bathroom, and whenever that toilet is flushed, the
central server or cloud-computing system 64 will know that the
water usage at that time is associated with that toilet. Thus, the
central server or cloud-computing system 64 can track the water
usage of that toilet as well as each water-consumption application
in the home. This information can be correlated to water bills or
smart water meters so as to provide users with a breakdown of their
water usage.
[0097] According to some embodiments, sound, vibration, and/or
motion sensing components of the smart devices are used to detect
sound, vibration, and/or motion created by mice and other rodents
as well as by termites, cockroaches, and other insects
(collectively referred to as "pests"). Based on the detected sound,
vibration, and/or motion, the central server or cloud-computing
system 64 makes inferences about pest-detection in the home and
provides related services. For example, the central server or
cloud-computing architecture 64 can run programs/algorithms that
recognize what certain pests sound like, how they move, and/or the
vibration they create, individually and/or collectively. According
to one embodiment, the central server or cloud-computing system 64
can determine the "signatures" of particular types of pests.
[0098] For example, in the event the central server or
cloud-computing system 64 detects sounds that may be associated
with pests, it notifies the occupants of such sounds and suggests
hiring a pest control company. If it is confirmed that pests are
indeed present, the occupants input to the central server or
cloud-computing system 64 confirms that its detection was correct,
along with details regarding the identified pests, such as name,
type, description, location, quantity, etc. This enables the
central server or cloud-computing system 64 to "tune" itself for
better detection and create "signatures" or "fingerprints" for
specific types of pests. For example, the central server or
cloud-computing system 64 can use the tuning as well as the
signatures and fingerprints to detect pests in other homes, such as
nearby homes that may be experiencing problems with the same pests.
Further, for example, in the event that two or more homes in a
"neighborhood" are experiencing problems with the same or similar
types of pests, the central server or cloud-computing system 64 can
make inferences that nearby homes may also have such problems or
may be susceptible to having such problems, and it can send warning
messages to those homes to help facilitate early detection and
prevention.
[0099] In some embodiments, to encourage innovation and research
and to increase products and services available to users, the
devices and services platform 80 expose a range of application
programming interfaces (APIs) 90 to third parties, such as
charities 94, governmental entities 96 (e.g., the Food and Drug
Administration or the Environmental Protection Agency), academic
institutions 98 (e.g., university researchers), businesses 100
(e.g., providing device warranties or service to related equipment,
targeting advertisements based on home data), utility companies
102, and other third parties. The APIs 90 are coupled to and permit
third-party systems to communicate with the central server or the
cloud-computing system 64, including the services 84, the
processing engine 86, the home data 82, and the derived home data
88. For example, the APIs 90 allow applications executed by the
third parties to initiate specific data processing tasks that are
executed by the central server or the cloud-computing system 64, as
well as to receive dynamic updates to the home data 82 and the
derived home data 88.
[0100] For example, third parties can develop programs and/or
applications, such as web or mobile apps, that integrate with the
central server or the cloud-computing system 64 to provide services
and information to users. Such programs and application may be, for
example, designed to help users reduce energy consumption, to
preemptively service faulty equipment, to prepare for high service
demands, to track past service performance, etc., or to perform any
of a variety of beneficial functions or tasks now known or
hereinafter developed.
[0101] According to some embodiments, third-party applications make
inferences from the home data 82 and the derived home data 88, such
inferences may include when are occupants home, when are they
sleeping, when are they cooking, when are they in the den watching
television, and when do they shower. The answers to these questions
may help third-parties benefit consumers by providing them with
interesting information, products and services as well as with
providing them with targeted advertisements.
[0102] In one example, a shipping company creates an application
that makes inferences regarding when people are at home. The
application uses the inferences to schedule deliveries for times
when people will most likely be at home. The application can also
build delivery routes around these scheduled times. This reduces
the number of instances where the shipping company has to make
multiple attempts to deliver packages, and it reduces the number of
times consumers have to pick up their packages from the shipping
company.
[0103] To further illustrate, FIG. 4 describes an abstracted
functional view 110 of the extensible devices and services platform
80 of FIG. 3, with particular reference to the processing engine 86
as well as devices, such as those of the smart-home environment 30
of FIG. 2. Even though devices situated in smart-home environments
will have an endless variety of different individual capabilities
and limitations, they can all be thought of as sharing common
characteristics in that each of them is a data consumer 112 (DC), a
data source 114 (DS), a services consumer 116 (SC), and a services
source 118 (SS). Advantageously, in addition to providing the
essential control information needed for the devices to achieve
their local and immediate objectives, the extensible devices and
services platform 80 can also be configured to harness the large
amount of data that is flowing out of these devices. In addition to
enhancing or optimizing the actual operation of the devices
themselves with respect to their immediate functions, the
extensible devices and services platform 80 can be directed to
"repurposing" that data in a variety of automated, extensible,
flexible, and/or scalable ways to achieve a variety of useful
objectives. These objectives may be predefined or adaptively
identified based on, e.g., usage patterns, device efficiency,
and/or user input (e.g., requesting specific functionality).
[0104] For example, FIG. 4 shows processing engine 86 as including
a number of paradigms 120. Processing engine 86 can include a
managed services paradigm 120a that monitors and manages primary or
secondary device functions. The device functions can include
ensuring proper operation of a device given user inputs, estimating
that (e.g., and responding to an instance in which) an intruder is
or is attempting to be in a dwelling, detecting a failure of
equipment coupled to the device (e.g., a light bulb having burned
out), implementing or otherwise responding to energy demand
response events, or alerting a user of a current or predicted
future event or characteristic. Processing engine 86 can further
include an advertising/communication paradigm 120b that estimates
characteristics (e.g., demographic information), desires and/or
products of interest of a user based on device usage. Services,
promotions, products or upgrades can then be offered or
automatically provided to the user. Processing engine 86 can
further include a social paradigm 120c that uses information from a
social network, provides information to a social network (for
example, based on device usage), and/or processes data associated
with user and/or device interactions with the social network
platform. For example, a user's status as reported to their trusted
contacts on the social network could be updated to indicate when
they are home based on light detection, security system
inactivation or device usage detectors. As another example, a user
may be able to share device-usage statistics with other users. In
yet another example, a user may share HVAC settings that result in
low power bills and other users may download the HVAC settings to
their smart thermostat 46 to reduce their power bills.
[0105] The processing engine 86 can include a
challenges/rules/compliance/rewards paradigm 120d that informs a
user of challenges, competitions, rules, compliance regulations
and/or rewards and/or that uses operation data to determine whether
a challenge has been met, a rule or regulation has been complied
with and/or a reward has been earned. The challenges, rules or
regulations can relate to efforts to conserve energy, to live
safely (e.g., reducing exposure to toxins or carcinogens), to
conserve money and/or equipment life, to improve health, etc. For
example, one challenge may involve participants turning down their
thermostat by one degree for one week. Those that successfully
complete the challenge are rewarded, such as by coupons, virtual
currency, status, etc. Regarding compliance, an example involves a
rental-property owner making a rule that no renters are permitted
to access certain owner's rooms. The devices in the room having
occupancy sensors could send updates to the owner when the room is
accessed.
[0106] The processing engine 86 can integrate or otherwise utilize
extrinsic information 122 from extrinsic sources to improve the
functioning of one or more processing paradigms. Extrinsic
information 122 can be used to interpret data received from a
device, to determine a characteristic of the environment near the
device (e.g., outside a structure that the device is enclosed in),
to determine services or products available to the user, to
identify a social network or social-network information, to
determine contact information of entities (e.g., public-service
entities such as an emergency-response team, the police or a
hospital) near the device, etc., to identify statistical or
environmental conditions, trends or other information associated
with a home or neighborhood, and so forth.
[0107] An extraordinary range and variety of benefits can be
brought about by, and fit within the scope of, the described
extensible devices and services platform 80, ranging from the
ordinary to the profound. Thus, in one "ordinary" example, each
bedroom of the smart-home environment 30 can be provided with a
smart wall switch 54, a smart wall plug 56, and/or smart hazard
detectors 50, all or some of which include an occupancy sensor,
wherein the occupancy sensor is also capable of inferring (e.g., by
virtue of motion detection, facial recognition, audible sound
patterns, etc.) whether the occupant is asleep or awake. If a
serious fire event is sensed, the remote security/monitoring
service or fire department is advised of how many occupants there
are in each bedroom, and whether those occupants are still asleep
(or immobile) or whether they have properly evacuated the bedroom.
While this is, of course, a very advantageous capability
accommodated by the described extensible devices and services
platform 80, there can be substantially more "profound" examples
that can truly illustrate the potential of a larger "intelligence"
that can be made available. By way of perhaps a more "profound"
example, the same bedroom occupancy data that is being used for
fire safety can also be "repurposed" by the processing engine 86 in
the context of a social paradigm of neighborhood child development
and education. Thus, for example, the same bedroom occupancy and
motion data discussed in the "ordinary" example can be collected
and made available (properly anonymized) for processing in which
the sleep patterns of schoolchildren in a particular ZIP code can
be identified and tracked. Localized variations in the sleeping
patterns of the schoolchildren may be identified and correlated,
for example, to different nutrition programs in local schools.
[0108] As previously discussed, the described extensible devices
and services platform 80 may enable communicating emergency
information between smart-home environments 30 that are linked
and/or to the proper authorities. For example, when a burglar
breaks into a smart-home environment 30, a home security system may
trip and sound an alarm and/or send emergency notifications to the
neighbors, the police, the security company, and the like.
Device Synchronization Overview
[0109] As discussed above, the cloud-computing system 64 may
receive data from devices of the smart-home environment 30 for
various purposes such as indexing, analysis, generating statistics,
and the like. However, since each device 10 sending data to the
cloud-computing system 64 may be communicating using a different
communication protocol, the data received by the cloud-computing
system 64 may be in different formats. To facilitate performing
various types of operations on the received data, the
cloud-computing system 64 may convert the data received via one
type of communication protocol into a format interpretable by
another type of communication protocol. In this way, the data
acquired by various devices disposed within the smart-home
environment 30 may be interpretable, and thus useful, to the
cloud-computing device 64.
[0110] Keeping this in mind, FIG. 5 illustrates a block diagram of
communication system 130 that may facilitate communication between
the cloud-computing system 64 and various types of devices disposed
in the smart-home environment 30. The cloud-computing system 64 may
be part of the extensible devices and services platform 80, which
may perform various types of analyses on the data received from the
different devices 10 in the smart-home environment 30.
[0111] Example devices that communicate with the cloud-computing
system 64 may include the portable electronic device (e.g.,
smartphone) 66, thermostat 46, hazard detector 50, space heater
132, and the like. In certain embodiments, the portable electronic
device 66 and the thermostat 46 may communicate with the
cloud-computing system 64 using one communication protocol, while
the hazard detector 50 may communicate with the cloud-computing
system 64 using a different communication protocol. In some cases,
the space heater 132 may communicate with just one device such as
the thermostat 46. As such, the thermostat 46 may be used as an
intermediary to communicate between the cloud-computing system 64
and the space heater 132.
[0112] In any case, the cloud-computing system 64 may receive two
different types of data via the two different communication
protocols. The cloud-computing system 64 may translate one or both
of the received data types into one format that may be
interpretable by the cloud-computing system 64. That is, the
cloud-computing system 64 may translate the received data, such
that all of the received data may be analyzed together. Additional
details regarding the translation operations performed by the
cloud-computing system 64 will be described below.
[0113] By way of example, one communication protocol employed by
the portable electronic device 66 and the thermostat 46 may be a
JavaScript Object Notation-based (JSON-based) protocol that sends
data organized as part of information buckets or a data type that
groups objects together according to some general field. The JSON
format is an open standard format that uses human-readable text to
transmit data objects consisting of field--value pairs.
[0114] Another example communication protocol that may be used by
the hazard detector 50 may include a type-length-value (TLV)
protocol. The TLV protocol may correspond to a data communication
protocol that encodes data according to a type of data, a length of
a value associated with the data, and the value of the data.
Generally, the type of the TLV protocol may include a binary code
that indicates a type of field that the data represents, the length
may include a size of the value field (typically in bytes), and the
value may represent a variable-sized series of bytes that contains
the data. By sending data in a TLV format, the data may be
compactly and flexibly transmitted using low encode/decode and
memory overhead, thereby providing an power efficient means of
communication.
JSON-Based Communication
[0115] Keeping the foregoing in mind, FIG. 6 illustrates an example
of a network-based communication system 140 that may use a
JSON-based communication protocol to communicate between a remote
server 142 (e.g., cloud-computing system 64) and client devices 144
(e.g., device 10). Referring to FIG. 6, the communication system
140 may be used for various purposes, including, for example,
synchronizing states of devices distributed across the system. As
such, the communication system 140 includes a remote server 142
that is remote from and communicatively coupled to one or more
client devices 144 via a network 146. The client devices 144 may
include one or more monitoring devices 148 and one or more access
devices 150.
[0116] Generally, the monitoring device 148 may be an electronic
device operable to generate base data to be shared across the
communication system 140. In one embodiment, the monitoring device
148 may generate such base data by monitoring one or more aspects
of its environment and using the monitored data as base data. For
example, where monitoring device 148 corresponds to the thermostat
46, the monitoring device 148 may include sensors that sense
environmental characteristics such as temperature, humidity,
occupancy, etc. Such data may thus be generated by monitoring
device 148 and communicated to remote server 142. When changes are
made at the monitoring device 148, for example, when environmental
changes are sensed, those changes may similarly be communicated to
remote server 142.
[0117] In addition to generating data by monitoring aspects of its
environments, data may also be generated by user interaction with
the monitoring device 148. For example, where monitoring device 148
corresponds to thermostat 46, a user may define a desired
temperature (i.e., a "set point temperature" or more simply "set
point") via the monitoring device 148, where the monitoring device
148 may subsequently control an electrically coupled HVAC system to
achieve and/or maintain the desired temperature. Or, via algorithms
programmed therein, monitoring device 148 themselves may generate a
set point. The set point, regardless of how it is generated or
altered, and changes thereto, may similarly be communicated to the
remote server 142.
[0118] Conversely, the remote server 142 may change one or more
fields of data associated with the monitoring device 148. For
example, the remote server 142 may wish to alter the set point
stored at the monitoring device 148. In such case, the remote
server 142 may alter its own version of the set point of the
monitoring device 148 and communicate that change to the monitoring
device 148. Thus, in addition to changes to data made at the
monitoring device 148 being reflected at the remote server 142,
changes to data made at the remote server 142 are reflected at the
monitoring device 148.
[0119] In some embodiments, an access device 150 may also be
provided, where the access device 150 can operate to access data
from and change data at the monitoring device 148. To access data
from the monitoring device 148, the access device 150 may acquire
copies of such data from the remote server 142. Since the state of
information at the monitoring device 148 and the state of
information at the remote server 142 are generally identical, by
acquiring the data from the remote server 142 the state of
information at the access device 150 is generally identical to that
at the monitoring device 148. Further, to change data of the
monitoring device 148 (e.g., the set point), a user may cause the
change at the access device 150, where the change is propagated to
the monitoring device 148 via the remote server 142.
[0120] In any case, multiple monitoring devices 148 and access
devices 150 may share its information or data with other monitoring
devices 148, access devices 150, or the remote server 142 via
network 146. The network 146 is any suitable network for enabling
communications between various entities, such as between client
devices 144 and remote server 142. Such a network may include, for
example, a local area network, a wide-area network, a virtual
private network, the Internet, an intranet, an extranet, a public
switched telephone network, an infrared network, a wireless
network, a wireless data network, a cellular network, or any other
such network or combination thereof. The network may, furthermore,
incorporate any suitable network topology. The network 146 may
utilize any suitable protocol, and communication over the network
146 may be enabled by wired or wireless connections, and
combinations thereof.
[0121] It should be noted that the communication system 140 may be
a distributed computing environment utilizing several computer
systems and components that are interconnected via communication
links, using one or more computer networks or direct connections.
However, it will be appreciated by those skilled in the art that
such a system could operate equally well in a system having fewer
or a greater number of components than are illustrated in FIG. 6.
Thus, the depiction of system 140 in FIG. 6 should be taken as
being illustrative in nature, and not as limiting the scope of the
present teachings.
[0122] FIG. 7 illustrates the communication system of FIG. 6
together with buckets of information provided at each of the
entities of that system according to an embodiment. As mentioned
above, the entities of system 140 may store data in a JSON-based
format that may take the form of "buckets." Each bucket of
information may include a field-value pair. The fields may be
defined for various properties of the monitoring device 148 and/or
its environment, while the value may be characteristic associated
with each field. For example, the thermostat 46 may include an
exemplary field-value pair of:
"hvac_heater_state": 0
[0123] The string "hvac_heater state" is the field, referring to
the state of an HVAC heater, and number "0" is the value, referring
to the state of the HVAC heater (e.g., off). With this field-value
pair example in mind, an exemplary bucket may be as follows:
TABLE-US-00001 Bucket Name: structure.<id> { "devices":
[device.<id>, device.<id>] "name": "My Living Room
Thermostat", "away": false, "display_location": "Palo Alto,CA\n"
}
[0124] Referring to the example above, the bucket is called
"structure" and includes field-value pairs associated with a
structure (e.g., house) in which the monitoring device 148 is
located. With reference to FIG. 7, the "structure" bucket may be
bucket "B1" 148A that includes values initially defined at the
monitoring device 148. Each bucket may be provided with a version
identifier and/or a timestamp. The version identifier uniquely
identifies a version of the bucket, whereas the timestamp
identifies a time at which a bucket (or value therein) was received
or generated by server 142. Thus, with reference once again to FIG.
7, the bucket "B1" may be associated with a unique version "v1" and
timestamp "t1" that are received from server 142.
[0125] The monitoring device 148 may have a plurality of buckets,
"B1" 148A through "BN" 148N, where each bucket includes its own set
of field-value pairs. The remote server 142 may also have a
plurality of buckets, "B1" 142A through "BN" 142N, that
respectively correspond to the buckets of the monitoring device
148. As such, when in steady state, the contents of the buckets at
the remote server 142 and the corresponding buckets at the
monitoring device 148 will be identical. In embodiments where
version identifiers and/or timestamps are used, the version
identifiers and/or timestamps of the buckets at the remote server
142 and the corresponding buckets at the monitoring device 148 will
similarly be identical.
[0126] As described, in some embodiments, the communication system
140 includes one or more access devices 150. The access device 150
similarly includes buckets "B1" 150A through "BN" 150N that
respectively correspond to the buckets of the monitoring device
148. When in steady state, the contents of the buckets at the
access device 150 and the corresponding buckets at each of the
remote server 142 and the monitoring device 148 will be identical.
In embodiments where version identifiers and/or timestamps are
used, the version identifiers and/or timestamps of the buckets at
the access device 150 will similarly be identical to those at the
remote server 142 and the monitoring device 148.
[0127] In at least one embodiment, a plurality of monitoring
devices 148 all associated with a same structure or user account
may be provided. Each monitoring device 148 includes its unique set
of buckets B1 through BN (where N may be the same or different for
across the devices 148) that are synchronized with the remote
server 142 and, in some cases with the access device 150. Further,
some or all of the monitoring devices 148 may include a shared
bucket "BS" 148S. The shared bucket BS is like other buckets, but
also may be shared or otherwise synchronized among multiple
monitoring devices 148 associated with the same structure or user
account. To facilitate such sharing, the remote server 142 may also
include the shared bucket "BS" 142S for each monitoring device 148.
When one monitoring device 148 makes changes to its shared bucket
"BS", the remote server 142 may propagate those changes to the
other monitoring devices 148. In this fashion, monitoring devices
148 may effectively communicate with one another.
[0128] An access device 150 may also include a shared bucket "BS"
150S. In at least one embodiment, the access device 150 includes
the shared bucket "BS" of all monitoring devices 148. In this
fashion, the access device 150 may be operable to access the
buckets of information that are shared across multiple monitoring
devices 148. Further details and examples of shared buckets are
described in U.S. Prov. Ser. No. 61/627,996 filed Oct. 21, 2011 and
as described in U.S. Ser. No. 13/624,892, entitled
"Subscription-Notification Mechanisms for Synchronization of
Distributed States," which are both incorporated by reference. One
such example includes so-called away-state flags, each
corresponding to a distinct occupancy-sensing device in a home,
each being set to an "away ready" state by the corresponding device
if it has not detected occupancy for a predetermined time interval,
wherein no one device will enter into an actual away state (a low
energy-usage state) until all of the flags are set to "away-ready."
For the exemplary case of occupancy-sensing thermostats this will
ensure that none of the thermostats will enter into a less
comfortable low energy-usage state until all of the devices have
"seen" the requisite non-occupancy condition, thereby establishing
a high probability that the home is truly unoccupied.
[0129] FIG. 8 illustrates the system of FIG. 6 including some
simplified components of the remote server 142 according to an
embodiment. Like numbered entities are identical to those previous
described, and thus further description is omitted. Remote server
142 includes a registration server 152, a plurality of
synchronization servers 154A through 154M, a logging server 156,
and a storage element 158. The registration server 152,
synchronization servers 154A through 154M, and logging server 156
are communicatively coupled to the client devices 144 via network
146. The synchronization servers 154A through 154M are also
communicatively coupled to the registration server 152 and the
storage element 158.
[0130] As further described in more detail herein, the storage
element 158 may store a variety of information such as buckets 142A
through 142N and 142S for all users of the communication system
140. For example, with reference to FIG. 7, for each user of the
communication system 150 the storage element 158 may store all of
the buckets 142A through 142N and any shared buckets 142S. The
registration server 152 and synchronization servers 154A through
154M may then operate to ensure that the state of the buckets in
the storage element 158 is identical to the state of the buckets in
the associated client devices 144. The storage element 158 may also
or alternatively store authentication-related information. For
example, the storage element 158 may store assigned credentials,
default credentials, etc.
[0131] In some embodiments and as further described herein, the
registration server 152 acts as a first point of contact for the
client devices 144. For example, a monitoring device 148 may have a
location identifier (e.g., a URL) of the registration server 152
hardcoded therein so that on initialization or reconnect the
monitoring device 148 may always contact registration server 152.
Among other things, the registration server 152 may identify one of
the synchronization servers 154A through 154M, which is responsible
for synchronizing the buckets at the client devices 144 with the
buckets at the storage element 158, and provide the identity of the
selected synchronization server to the client devices 144. The
client devices 144 may then subsequently connect to the selected
synchronization server, which will subsequently synchronize the
states of the client devices 144 with each other (when, e.g., the
client devices 144 are associated with one another such as being
paired to the same user account) and with the storage element
158.
[0132] As shown above, the communication between the client devices
144 and the remoter server 142 may enable the client devices 144
and the remoter server 142 to share information that may be useful
in determining how to manage the condition of the smart-home
environment 30. Moreover, when sharing the data between the client
devices 144 and the remoter server 142, it is useful that the data
is sent and stored by the client devices 144 and the remoter server
142 in a format that is interpretable by the client devices 144 and
the remoter server 142. Here, the client devices 144 and the
remoter server 142 both use data configured in the bucket format
described above.
[0133] In certain embodiments, the data received from the client
devices 144 may be stored by the remote server 142 in the storage
element 158. FIG. 9 illustrates example buckets of information that
may be part of the storage element 158. For example, the storage
element 158 may include, for each client device 144, a plurality of
buckets that corresponds to the data received from each client
device 144. For a client device 144, "Device A," the storage
element 158 includes buckets 190, which include "Bucket A," "Bucket
B," "Bucket C," "Bucket Z," and "BucketS." Device A may be paired
to, or otherwise associated with, a user account for "User A." In
this particular example, User A is associated with two devices,
Device A and Device B. Storage element 158 includes buckets 160
associated with Device A, and includes buckets 162 associated with
Device B. Other users, such as User Band User C, are associated
with other buckets 164 and 166. BucketS in this example is a bucket
that is shared between Device A and Device B.
[0134] In certain embodiments, the buckets described above may be
defined according to a JSON protocol. As such, the remote server
142 may update a particular bucket in the storage element 158 to
include the data acquired from the client devices 144 in a JSON
format. Since the data stored in the storage element 158
corresponds to one format (e.g., JSON), the remote server 142 may
perform various types of analyses on the aggregate data received
from all of the client devices 144 to determine certain
modifications for the respective client devices 144 and the
like.
TLV-Based Communication
[0135] Although certain devices may communicate using the buckets
of information and the JSON-based protocol described above, in some
embodiments, other devices may communicate using a TLV-based
protocol mentioned above. As such, these other devices may send
data to the remote server 142 in a TLV format. To ensure that the
data received from these other devices are interpretable by the
remote server 142 or by any other device that analyzes the data,
the remote server 142 may translate the TLV-format data into a
JSON-format that provides a corresponding bucket for the TLV-format
data. In the same manner, the remote server 142 may send data to
each respective device according to a format that is interpretable
by the respective device.
[0136] With this in mind, communicating using the TLV-format may
enable devices to efficiently communication through a fabric
network of devices in a home environment or similar environment.
For example, the TLV-format communication may balance power and
reliability concerns regarding the communication, may efficiently
communicate messages to certain preferred networks by analyzing
Internet Protocol version 6 (IPv6) packet headers that use an
Extended Unique Local Address (EULA), may efficiently communicate
software updates and status reports throughout a fabric network,
and/or may easily and efficiently join a fabric network.
[0137] For instance, an electronic device may include memory or
storage storing instructions to operate a network stack, a
processor to execute the instructions, and a network interface to
join a network-connected fabric of devices and communicate a
message to a target device of the fabric of devices using the
network stack. The network stack may include an application layer
to provide an application payload with data to be transmitted in
the message, a platform layer to encapsulate the application
payload in a general message format of the message, a transport
layer to selectably transport the message using either User
Datagram Protocol (UDP) or Transmission Control Protocol (TCP), and
a network layer to communicate the message using Internet Protocol
Version 6 (IPv6) via one or more networks. These networks may
include, for example, an 802.11 wireless network, an 802.15.4
wireless network, a powerline network, a cellular network, and/or
an Ethernet network. Moreover, the application layer, the platform
layer, the transport layer, and/or the network layer may determine
a property of the manner of communication of the message to the
target node based at least in part on a type of the message, the
network over which the message is to be sent, a distance over which
the message may travel through the fabric, power consumption
behavior of the electronic device, power consumption behavior of
the target device, and/or power consumption behavior of an
intervening device of the fabric of devices that is to communicate
the message between the electronic device and the target device.
Further, varying the property of the manner of communication may
cause the electronic device, the target device, and/or the
intervening device to consume different amounts of power and cause
the message to more reliably or less reliably reach the target
node.
[0138] To effectively and efficiently communicate data between each
other within the home environment, the TLV-format devices may use a
fabric network that includes one or more logical networks to manage
communication between the devices. That is, the efficient fabric
network may enable numerous devices within a home to communicate
with each other using one or more logical networks. The fabric
network may be supported by an efficient communication scheme
involving, for example, an efficient network layer, an efficient
platform layer, and/or an efficient application layer to manage
communication. The fabric network may support Internet Protocol
version 6 (IPv6) communication such that each connected device may
have a unique local address (ULA). In some examples, the IPv6
communications may employ an Extended Unique Local Address (EULA).
Moreover, to enable each device to integrate with a home, it may be
useful for each device to communicate within the network using low
amounts of power. That is, by enabling devices to communicate using
low power, the devices may be placed anywhere in a home without
being coupled to a continuous power source (e.g.,
battery-powered).
[0139] On a relatively lower layer of the communication protocol
(e.g., the network layer), the fabric efficient network layer may
establish a communication network in which numerous devices within
a home may communicate with each other via a wireless mesh network.
The communication network may support Internet Protocol version 6
(IPv6) communication such that each connected device may have a
unique Internet Protocol (IP) address. Moreover, to enable each
device to integrate with a home, it may be useful for each device
to communicate within the network using low amounts of power. That
is, by enabling devices to communicate using low power, the devices
may be placed anywhere in a home without being coupled to a
continuous power source.
[0140] The efficient network layer may thus establish a procedure
in which data may be transferred between two or more devices such
that the establishment of the communication network involves little
user input, the communication between devices involves little
energy, and the communication network, itself, is secure. In one
embodiment, the efficient network layer may be an IPv6-based
communication network that employs Routing Information
Protocol--Next Generation (RIPng) as its routing mechanism and a
Datagram Transport Layer Security (DTLS) protocol as its security
mechanism. As such, the efficient network layer may provide a
simple means for adding or removing devices to a home while
protecting the information communicated between the connected
devices.
[0141] On relatively higher layers of the communication protocol
(e.g., the platform and/or application layers), the fabric of
devices may be created and maintained. These layers may enable
parametric software updates and status reports throughout the
fabric. These layers may also provide communication that may be
aware of certain network power constraints, such as the power
constraints of "sleepy" or battery-powered devices, and may
communicate messages with these factors in mind.
[0142] Keeping the foregoing in mind, the TLV-format devices may
communicate with each other and the remote server 142 using a
typical message format that enables the devices to understand
communications between the devices regardless of which logical
networks the communicating devices are connected to in the fabric.
Within the message format, a payload of data may be included for
the receiving device to store and/or process. The format and the
contents of the payload may vary according to a header within the
payload that indicates a profile (including one or more protocols)
and/or a type of message that is being sent according to the
profile.
[0143] According to some embodiments, two or more TLV-format
devices in a fabric may communicate using status reporting
protocols or profiles. For example, in certain embodiments, a
status reporting protocol or schema may be included in a core
profile that is available to devices connected to the fabric. Using
the status reporting protocol, the TLV-format devices may send or
request status information to or from other TLV-format devices in
the fabric.
[0144] Similarly, in certain embodiments, two or more TLV-format
devices in a fabric may communicate using update software protocols
or profiles. In some embodiments, the update software protocol or
schema may be included in a core profile that is available to
TLV-format devices connected to the fabric. Using the update
software protocol, the TLV-format devices may request, send, or
notify the presence of updates within the fabric.
[0145] In certain embodiments, two or more TLV-format devices in a
fabric may communicate using data management protocols or profiles.
In some embodiments, the data management protocol or schema may be
included in a core profile that is available to devices connected
to the fabric. Using the update data management protocol, devices
may request, view, or track node-resident information that is
stored in other devices.
[0146] Furthermore, in certain embodiments, two or more TLV-format
devices in a fabric may transfer data using bulk data transfer
protocols or profiles. In some embodiments, the bulk data transfer
protocol or schema may be included in a core profile that is
available to devices connected to the fabric. Using the bulk data
transfer protocol, devices may initiate, send, or receive bulk data
using any logical networks in the fabric. In certain embodiments,
either a sending or a receiving device using the bulk data transfer
protocol may be able to "drive" a synchronous transfer between the
devices. In other embodiments, the bulk transfer may be performed
with an asynchronous transfer.
[0147] Generally, the TLV-format devices may communicate with each
other using an efficient low-power wireless personal network
(ELoWPAN) as described in U.S. Ser. No. 13/926,335, entitled
"Efficient Communication for Devices of a Home Network," which is
herein incorporated by reference. The ELowPAN may define an
efficient network layer that may be part of an Open Systems
Interconnection (OSI) model 170 as depicted in FIG. 10. The OSI
model 170 illustrates functions of a communication system with
respect to abstraction layers. That is, the OSI model may specify a
networking framework or how communications between devices may be
implemented. In one embodiment, the OSI model may include six
layers: a physical layer 172, a data link layer 174, a network
layer 176, a transport layer 178, a platform layer 180, and an
application layer 182. Generally, each layer in the OSI model 170
may serve the layer above it and may be served by the layer below
it. In at least some embodiments, a higher layer may be agnostic to
technologies used in lower layers. For example, in certain
embodiments, the platform layer 180 may be agnostic to the network
type used in the network layer 176.
[0148] Keeping this in mind, the physical layer 172 may provide
hardware specifications for devices that may communicate with each
other. As such, the physical layer 172 may establish how devices
may connect to each other, assist in managing how communication
resources may be shared between devices, and the like.
[0149] The data link layer 174 may specify how data may be
transferred between devices. Generally, the data link layer 174 may
provide a way in which data packets being transmitted may be
encoded and decoded into bits as part of a transmission
protocol.
[0150] The network layer 176 may specify how the data being
transferred to a destination node is routed. The network layer 176
may also provide a security protocol that may maintain the
integrity of the data being transferred.
[0151] The transport layer 178 may specify a transparent transfer
of the data from a source node to a destination node. The transport
layer 178 may also control how the transparent transfer of the data
remains reliable. As such, the transport layer 178 may be used to
verify that data packets intended to transfer to the destination
node indeed reached the destination node. Example protocols that
may be employed in the transport layer 98 may include Transmission
Control Protocol (TCP) and User Datagram Protocol (UDP).
[0152] The platform layer 180 may establish connections between
devices according to the protocol specified within the transport
layer 178. The platform layer 180 may also translate the data
packets into a form that the application layer 172 may use. The
application layer 172 may support a software application that may
directly interface with the user. As such, the application layer
172 may implement protocols defined by the software application.
For example, the software application may provide serves such as
file transfers, electronic mail, and the like.
Efficient Network Layer
[0153] Referring now to FIG. 11, in one embodiment, the network
layer 176 and the transport layer 178 may be configured in a
certain manner to form an efficient low power wireless personal
network (ELoWPAN) 190. In one embodiment, the ELoWPAN 190 may be
based on an IEEE 802.15.4 network, which may correspond to low-rate
wireless personal area networks (LR-WPANs). The ELoWPAN 190 may
specify that the network layer 176 may route data between the
devices 10 in the home environment 30 using a communication
protocol based on Internet Protocol version 6 (IPv6). As such, each
device 10 may include a 128-bit IPv6 address that may provide each
device 10 with a unique address to use to identify itself over the
Internet, a local network around the home environment 30, or the
like.
[0154] In one embodiment, the network layer 176 may specify that
data may be routed between devices using Routing Information
Protocol--Next Generation (RIPng). RIPng is a routing protocol that
routes data via a wireless mesh network based on a number of hops
between the source node and the destination node. That is, RIPng
may determine a route to the destination node from the source node
that employs the least number of hops when determining how the data
will be routed. In addition to supporting data transfers via a
wireless mesh network, RIPng is capable of supporting IPv6
networking traffic. As such, each device 10 may use a unique IPv6
address to identify itself and a unique IPv6 address to identify a
destination node when routing data.
[0155] As mentioned above, the network layer 176 may also provide a
security protocol that may manage the integrity of the data being
transferred. Here, the efficient network layer may secure data
transferred between devices using a Datagram Transport Layer
Security (DTLS) protocol. Generally, Transport Layer Security (TLS)
protocol is commonly used to protect data transfers via the
Internet. However, in order for the TLS protocol to be effective,
the TLS protocol may transport data using a reliable transport
channel such as Transmission Control Protocol (TCP). DTLS provides
a similar level of security for transferred data while supporting
unreliable transport channels such as User Datagram Protocol
(UDP).
[0156] The network layer 176 depicted in FIG. 11 is characterized
herein as the efficient network layer mentioned above. That is the
efficient network layer routes IPv6 data using RIPng and secures
the routed data using the DTLS protocol. Since the efficient
network layer uses the DTLS protocol to secure data transfer
between devices, the transport layer 178 may support TCP and UDP
transfer schemes for the data.
[0157] Using the above-described ELowPAN 190 and/or any other
suitable IPv6 logical networks, efficient platform and/or
application layers may be used to generate the fabric of devices in
a home environment or similar environments, as mentioned above. The
fabric of devices may enable many generally local devices (e.g.,
TLV-format devices) to communicate, sharing data and information,
invoking methods on one another, parametrically providing software
updates through the network, and generally communicating messages
in an efficient, power-conscious way.
Fabric--Device Interconnection
[0158] As discussed above, a fabric may be implemented using one or
more suitable communications protocols, such as IPv6 protocols. In
fact, the fabric may be partially or completely agnostic to the
underlying technologies (e.g., network types or communication
protocols) used to implement the fabric. Within the one or more
communications protocols, the fabric may be implemented using one
or more network types used to communicatively couple electrical
devices using wireless or wired connections. For example, certain
embodiments of the fabric may include Ethernet, WiFi, 802.15.4,
ZigBee.RTM., ISA100.11a, WirelessHART, MiWi.TM., power-line
networks, and/or other suitable network types. Within the fabric
devices (e.g., nodes) can exchange packets of information with
other devices (e.g., nodes) in the fabric, either directly or via
intermediary nodes, such as intelligent thermostats, acting as IP
routers. These nodes may include manufacturer devices (e.g.,
thermostats and smoke detectors) and/or customer devices (e.g.,
phones, tablets, computers, etc.). Additionally, some devices may
be "always on" and continuously powered using electrical
connections. Other devices may have partially reduced power usage
(e.g., medium duty cycle) using a reduced/intermittent power
connection, such as a thermostat or doorbell power connection.
Finally, some devices may have a short duty cycle and run solely on
battery power. In other words, in certain embodiments, the fabric
may include heterogeneous devices that may be connected to one or
more sub-networks according to connection type and/or desired power
usage.
Fabric Network Connection to Services
[0159] In addition to communications between devices within the
home, a fabric may include services that may be located physically
near other devices in the fabric or physically remote from such
devices. In certain embodiments, the services may be provided via
the remote server 142 described above. The fabric connects to these
services through one or more service end points. FIG. 12
illustrates an embodiment of a service 198 communicating with
fabrics 196, 198, and 200. The service 194 may include various
services that may be used by devices in fabrics 196, 198, and/or
200. For example, in some embodiments, the service 194 may be a
time of day service that supplies a time of day to devices, a
weather service to provide various weather data (e.g., outside
temperature, sunset, wind information, weather forecast, etc.), an
echo service that "pings" each device, data management services,
device management services, and/or other suitable services. As
illustrated, the service 194 may include a server 202 (e.g., web
server) that stores/accesses relevant data and passes the
information through a service end point 194 to one or more end
points 196 in a fabric, such as fabric 196. Although the
illustrated embodiment only includes three fabrics with a single
server 202, it should be appreciated that the service 196 may
connect to any number of fabrics and may include servers in
addition to the server 202 and/or connections to additional
services.
[0160] In certain embodiments, the service 194 may also connect to
a consumer device 208, such as a phone, tablet, and/or computer.
The consumer device 208 may be used to connect to the service 194
via a fabric, such as fabric 196, an Internet connection, and/or
some other suitable connection method. The consumer device 208 may
be used to access data from one or more end points (e.g.,
electronic devices) in a fabric either directly through the fabric
or via the service 194. In other words, using the service 194, the
consumer device 208 may be used to access/manage devices in a
fabric remotely from the fabric.
Communication Between Devices in a Fabric
[0161] As discussed above, each electronic device or node may
communicate with any other node in the fabric, either directly or
indirectly depending upon fabric topology and network connection
types. Additionally, some devices (e.g., remote devices) may
communicate through a service (e.g., remote server 142) to
communicate with other devices in the fabric. FIG. 13 illustrates
an embodiment of a communication 210 between two devices 212 and
214. The communication 210 may span one or more networks either
directly or indirectly through additional devices and/or services,
as described above. Additionally, the communication 210 may occur
over an appropriate communication protocol, such as IPv6, using one
or more transport protocols. For example, in some embodiments the
communication 210 may include using the transmission control
protocol (TCP) and/or the user datagram protocol (UDP). In some
embodiments, the device 212 may transmit a first signal 216 to the
device 214 using a connectionless protocol (e.g., UDP). In certain
embodiments, the device 212 may communicate with the device 214
using a connection-oriented protocol (e.g., TCP). Although the
illustrated communication 210 is depicted as a bi-directional
connection, in some embodiments, the communication 210 may be a
uni-directional broadcast.
Data Transmitted in the Fabric
[0162] Data passed through the fabric may be arranged in a format
common to all messages and/or common to specific types of
conversations in the fabric. The message format may correspond to a
TLV format mentioned above. In some embodiments, the TLV-format may
have a one-to-one mapping to a JSON format to enable the remote
server 142 or cloud-computing system 64 to store data received from
each device 10 of the smart-home environment 30 in a uniform manner
and with respect to corresponding buckets of information. Although
the following data frames are described as including specific
sizes, it should be noted that lengths of the data fields in the
data frames may be varied to other suitable bit-lengths.
A. Security
[0163] Along with data intended to be transferred, the fabric may
transfer the data with additional security measures such as
encryption, message integrity checks, and digital signatures. In
some embodiments, a level of security supported for a device may
vary according to physical security of the device and/or
capabilities of the device. In certain embodiments, messages sent
between nodes in the fabric may be encrypted using the Advanced
Encryption Standard (AES) block cipher operating in counter mode
(AES-CTR) with a 128-bit key. As discussed below, each message
contains a 32-bit message id. The message id may be combined with a
sending nodes id to form a nonce for the AES-CTR algorithm. The
32-bit counter enables 4 billion messages to be encrypted and sent
by each node before a new key is negotiated.
[0164] In some embodiments, the fabric may insure message integrity
using a message authentication code, such as HMAC-SHA-1, that may
be included in each encrypted message. In some embodiments, the
message authentication code may be generated using a 160-bit
message integrity key that is paired one-to-one with the encryption
key. Additionally, each node may check the message id of incoming
messages against a list of recently received ids maintained on a
node-by-node basis to block replay of the messages.
B. Tag Length Value (TLV) Formatting
[0165] To reduce power consumption, it is desirable to send at
least a portion of the data sent over the fabric that compactly
while enabling the data containers to flexibly represents data that
accommodates skipping data that is not recognized or understood by
skipping to the next location of data that is understood within a
serialization of the data. In certain embodiments, tag-length-value
(TLV) formatting, as mentioned above, may be used to compactly and
flexibly encode/decode data. By storing at least a portion of the
transmitted data in TLV, the data may be compactly and flexibly
stored/sent along with low encode/decode and memory overhead, as
discussed below in reference to Table 7. In certain embodiments,
TLV may be used for some data as flexible, extensible data, but
other portions of data that is not extensible may be stored and
sent in an understood standard protocol data unit (PDU).
[0166] Data formatted in a TLV format may be encoded as TLV
elements of various types, such as primitive types and container
types. Primitive types include data values in certain formats, such
as integers or strings. For example, the TLV format may encode: 1,
2, 3, 4, or 8 byte signed/unsigned integers, UTF-8 strings, byte
strings, single/double-precision floating numbers (e.g., IEEE
754-1985 format), Boolean, null, and other suitable data format
types. Container types include collections of elements that are
then sub-classified as container or primitive types. Container
types may be classified into various categories, such as
dictionaries, arrays, paths or other suitable types for grouping
TLV elements, known as members. A dictionary is a collection of
members each having distinct definitions and unique tags within the
dictionary. An array is an ordered collection of members with
implied definitions or no distinct definitions. A path is an
ordered collection of members that described how to traverse a tree
of TLV elements.
[0167] As illustrated in FIG. 14, an embodiment of a TLV packet 220
includes three data fields: a tag field 222, a length field 224,
and a value field 226. Although the illustrated fields 222, 224,
and 226 are illustrated as approximately equivalent in size, the
size of each field may be variable and vary in size in relation to
each other. In other embodiments, the TLV packet 220 may further
include a control byte before the tag field 222.
[0168] In embodiments having the control byte, the control byte may
be sub-divided into an element type field and a tag control field.
In some embodiments, the element type field includes 5 lower bits
of the control byte and the tag control field occupies the upper 3
bits. The element type field indicates the TLV element's type as
well as the how the length field 224 and value field 226 are
encoded. In certain embodiments, the element type field also
encodes Boolean values and/or null values for the TLV. For example,
an embodiment of an enumeration of element type field is provided
in Table 1 below.
TABLE-US-00002 TABLE 1 Example element type field values. 7 6 5 4 3
2 1 0 0 0 0 0 0 Signed Integer, 1 byte value value 0 0 0 0 1 Signed
Integer, 2 byte value 0 0 0 1 0 Signed Integer, 4 byte value 0 0 0
1 1 Signed Integer, 8 byte value 0 0 1 0 0 Unsigned Integer, 1 byte
value 0 0 1 0 1 Unsigned Integer, 2 byte value 0 0 1 1 0 Unsigned
Integer, 4 byte value 0 0 1 1 1 Unsigned Integer, 8 byte value 0 1
0 0 0 Boolean False 0 1 0 0 1 Boolean True 0 1 0 1 0 Floating Point
Number, 4 byte value 0 1 0 1 1 Floating Point Number, 8 byte value
0 1 1 0 0 UTF8-String, 1 byte length 0 1 1 0 1 UTF8-String, 2 byte
length 0 1 1 1 0 UTF8-String, 4 byte length 0 1 1 1 1 UTF8-String,
8 byte length 1 0 0 0 0 Byte String, 1 byte length 1 0 0 0 1 Byte
String, 2 byte length 1 0 0 1 0 Byte String, 4 byte length 1 0 0 1
1 Byte String, 8 byte length 1 0 1 0 0 Null 1 0 1 0 1 Dictionary 1
0 1 1 0 Array 1 0 1 1 1 Path 1 1 0 0 0 End of Container
[0169] The tag control field indicates a form of the tag in the tag
field 222 assigned to the TLV element (including a zero-length
tag). Examples, of tag control field values are provided in Table 2
below.
TABLE-US-00003 TABLE 2 Example values for tag control field. 7 6 5
4 3 2 1 0 0 0 0 Anonymous, 0 bytes 0 0 1 Context-specific Tag, 1
byte 0 1 0 Core Profile Tag, 2 bytes 0 1 1 Core Profile Tag, 4
bytes 1 0 0 Implicit Profile Tag, 2 bytes 1 0 1 Implicit Profile
Tag, 4 bytes 1 1 0 Fully-qualified Tag, 6 bytes 1 1 1
Fully-qualified Tag, 8 bytes
[0170] In other words, in embodiments having a control byte, the
control byte may indicate a length of the tag.
[0171] In certain embodiments, the tag field 222 may include zero
to eight bytes, such as eight, sixteen, thirty two, or sixty four
bits. In some embodiments, the tag of the tag field may be
classified as profile-specific tags or context-specific tags.
Profile-specific tags identify elements globally using a vendor Id,
a profile Id, and/or tag number as discussed below.
Context-specific tags identify TLV elements within a context of a
containing dictionary element and may include a single-byte tag
number. Since context-specific tags are defined in context of their
containers, a single context-specific tag may have different
interpretations when included in different containers. In some
embodiments, the context may also be derived from nested
containers.
[0172] In embodiments having the control byte, the tag length is
encoded in the tag control field and the tag field 222 includes a
possible three fields: a vendor Id field, a profile Id field, and a
tag number field. In the fully qualified form, the encoded tag
field 222 includes all three fields with the tag number field
including 16 or 32 bits determined by the tag control field. In the
implicit form, the tag includes only the tag number, and the vendor
Id and profile Id are inferred from the protocol context of the TLV
element. The core profile form includes profile-specific tags, as
discussed above. Context-specific tags are encoded as a single byte
conveying the tag number. Anonymous elements have zero-length tag
fields 222.
[0173] In some embodiments without a control byte, two bits may
indicate a length of the tag field 222, two bits may indicate a
length of the length field 224, and four bits may indicate a type
of information stored in the value field 226. An example of
possible encoding for the upper 8 bits for the tag field is
illustrated below in Table 3.
TABLE-US-00004 TABLE 3 Tag field of a TLV packet Byte 0 7 6 5 4 3 2
1 0 Description 0 0 -- -- -- -- -- -- Tag is 8 bits 0 1 -- -- -- --
-- -- Tag is 16 bits 1 0 -- -- -- -- -- -- Tag is 32 bits 1 1 -- --
-- -- -- -- Tag is 64 bits -- -- 0 0 -- -- -- -- Length is 8 bits
-- -- 0 1 -- -- -- -- Length is 16 bits -- -- 1 0 -- -- -- --
Length is 32 bits -- -- 1 1 -- -- -- -- Length is 64 bits -- -- 0 0
0 0 Boolean -- -- 0 0 0 1 Fixed 8-bit Unsigned -- -- 0 0 1 0 Fixed
8-bit Signed -- -- 0 0 1 1 Fixed 16-bit Unsigned -- -- 0 1 0 0
Fixed 16-bit Signed -- -- 0 1 0 1 Fixed 32-bit Unsigned -- -- 0 1 1
0 Fixed 32-bit Signed -- -- 0 1 1 1 Fixed 64-bit Unsigned -- -- 1 0
0 0 Fixed 64-bit Signed -- -- 1 0 0 1 32-bit Floating Point -- -- 1
0 1 0 64-bit Floating Point -- -- 1 0 1 1 UTF-8 String -- -- 1 1 0
0 Opaque Data -- -- 1 1 0 1 Container
[0174] As illustrated in Table 3, the upper 8 bits of the tag field
222 may be used to encode information about the tag field 222,
length field 224, and the value field 226, such that the tag field
222 may be used to determine length for the tag field 222 and the
length fields 224. Remaining bits in the tag field 222 may be made
available for user-allocated and/or user-assigned tag values.
[0175] The length field 224 may include eight, sixteen, thirty two,
or sixty four bits as indicated by the tag field 222 as illustrated
in Table 3 or the element field as illustrated in Table 2.
Moreover, the length field 224 may include an unsigned integer that
represents a length of the encoded in the value field 226. In some
embodiments, the length may be selected by a device sending the TLV
element. The value field 226 includes the payload data to be
decoded, but interpretation of the value field 226 may depend upon
the tag length fields, and/or control byte. For example, a TLV
packet without a control byte including an 8-bit tag is illustrated
in Table 4 below for illustration.
TABLE-US-00005 TABLE 4 Example of a TLV packet including an 8-bit
tag Tag Length Value Description 0x0d 0x24 0x09 0x04 0x42 95 00 00
74.5 0x09 0x04 0x42 98 66 66 76.2 0x09 0x04 0x42 94 99 9a 74.3 0x09
0x04 0x42 98 99 9a 76.3 0x09 0x04 0x42 95 33 33 74.6 0x09 0x04 0x42
98 33 33 76.1
[0176] As illustrated in Table 4, the first line indicates that the
tag field 222 and the length field 224 each have a length of 8
bits. Additionally, the tag field 222 indicates that the tag type
is for the first line is a container (e.g., the TLV packet). The
tag field 224 for lines two through six indicate that each entry in
the TLV packet has a tag field 222 and length field 224 consisting
of 8 bits each. Additionally, the tag field 224 indicates that each
entry in the TLV packet has a value field 226 that includes a
32-bit floating point. Each entry in the value field 226
corresponds to a floating number that may be decoded using the
corresponding tag field 222 and length field 224 information. As
illustrated in this example, each entry in the value field 226
corresponds to a temperature in Fahrenheit. As can be understood,
by storing data in a TLV packet as described above, data may be
transferred compactly while remaining flexible for varying lengths
and information as may be used by different devices in the fabric.
Moreover, in some embodiments, multi-byte integer fields may be
transmitted in little-endian order or big-endian order.
[0177] By transmitting TLV packets in using an order protocol
(e.g., little-endian) that may be used by sending/receiving device
formats (e.g., JSON), data transferred between nodes may be
transmitted in the order protocol used by at least one of the nodes
(e.g., little endian). For example, if one or more nodes include
ARM or ix86 processors, transmissions between the nodes may be
transmitted using little-endian byte ordering to reduce the use of
byte reordering. By reducing the inclusion of byte reordering, the
TLV format enable devices to communicate using less power than a
transmission that uses byte reordering on both ends of the
transmission. Furthermore, TLV formatting may be specified to
provide a one-to-one translation between other data storage
techniques, such as JSON+ Extensible Markup Language (XML). As an
example, the TLV format may be used to represent the following XML
Property List:
TABLE-US-00006 <?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple Computer//DTD PLIST 1.0//EN"
"http://www.apple.com/DTDs/PropertyList-1.0.dtd"> <plist
version="1.0"> <dict> <key>OfflineMode</key>
<false/> <key>Network</key> <dict>
<key>IPv4</key> <dict>
<key>Method</key> <string>dhcp</string>
</dict> <key>IPv6</key> <dict>
<key>Method</key> <string>auto</string>
</dict> </dict> <key>Technologies</key>
<dict> <key>wifi</key> <dict>
<key>Enabled</key> <true/>
<key>Devices</key> <dict>
<key>wifi_18b4300008b027</key> <dict>
<key>Enabled</key> <true/> </dict>
</dict> <key>Services</key> <array>
<string>wifi_18b4300008b027_3939382d33204 16c70696e652054657
272616365</string> </array> </dict>
<key>802.15.4</key> <dict>
<key>Enabled</key> <true/>
<key>Devices</key> <dict>
<key>802.15.4_18b43000000002fac4</key> <dict>
<key>Enabled</key> <true/> </dict>
</dict> <key>Services</key> <array>
<string>802.15.4_18b43000000002fac4_3
939382d3320416c70696e6520546572</string> </array>
</dict> </dict> <key>Services</key>
<dict>
<key>wifi_18b4300008b027_3939382d3320416c70696e652054657272616365&l-
t;/ key> <dict> <key>Name</key>
<string>998-3 Alpine Terrace</string>
<key>SSID</key>
<data>3939382d3320416c70696e652054657272616365 </data>
<key>Frequency</key>
<integer>2462</integer>
<key>AutoConnect</key> <true/>
<key>Favorite</key> <true/>
<key>Error</key> <string/>
<key>Network</key> <dict>
<key>IPv4</key> <dict>
<key>DHCP</key> <dict>
<key>LastAddress</key>
<data>0a02001e</data> </dict> </dict>
<key>IPv6</key> <dict/> </dict>
</dict>
<key>802.15.4_18b43000000002fac4_3939382d3320416c70696e652054
6572</key> <dict> <key>Name</key>
<string>998-3 Alpine Ter</string>
<key>EPANID</key>
<data>3939382d3320416c70696e6520546572</data>
<key>Frequency</key>
<integer>2412</integer>
<key>AutoConnect</key> <true/>
<key>Favorite</key> <true/>
<key>Error</key> <string/>
<key>Network</key> <dict/> </dict>
</dict> </dict> </plist
[0178] As an example, the above property list may be represented in
tags of the above-described TLV format (without a control byte)
according to Table 5 below.
TABLE-US-00007 TABLE 5 Example representation of the XML Property
List in TLV format XML Key Tag Type Tag Number OfflineMode Boolean
1 IPv4 Container 3 IPv6 Container 4 Method String 5 Technologies
Container 6 WiFi Container 7 802.15.4 Container 8 Enabled Boolean 9
Devices Container 10 ID String 11 Services Container 12 Name String
13 SSID Data 14 EPANID Data 15 Frequency 16-bit Unsigned 16
AutoConnect Boolean 17 Favorite Boolean 18 Error String 19 DHCP
String 20 LastAddress Data 21 Device Container 22 Service Container
23
[0179] Similarly, Table 6 illustrates an example of literal tag,
length, and value representations for the example XML Property
List.
TABLE-US-00008 TABLE 6 Example of literal values for tag, length,
and value fields for XML Property List Tag Length Value Description
0x40 01 0x01 0 OfflineMode 0x4d 02 0x14 Network 0x4d 03 0x07
Network.IPv4 0x4b 05 0x04 "dhcp" Network.IPv4.Method 0x4d 04 0x07
Network.IPv6 0x4b 05 0x04 "auto" Network.IPv6.Method 0x4d 06 0xd6
Technologies 0x4d 07 0x65 Technologies.wifi 0x40 09 0x01 1
Technologies.wifi.Enabled 0x4d 0a 0x5e Technologies.wifi.Devices
0x4d 16 0x5b Technologies.wifi.Devices.Device.[0] 0x4b 0b 0x13
"wifi_18b43 . . . " Technologies.wifi.Devices.Device.[0].ID 0x40 09
0x01 1 Technologies.wifi.Devices.Device.[0].Enabled 0x4d 0c 0x3e
Technologies.wifi.Devices.Device.[0].Services 0x0b 0x3c "wifi_18b43
. . . " Technologies.wifi.Devices.Device.[0].Services.[0] 0x4d 08
0x6b Technologies.802.15.4 0x40 09 0x01 1
Technologies.802.15.4.Enabled 0x4d 0a 0x64
Technologies.802.15.4.Devices 0x4d 16 0x61
Technologies.802.15.4.Devices.Device.[0] 0x4b 0b 0x1a "802.15.4_18
. . . " Technologies.802.15.4.Devices.Device. [0].ID 0x40 09 0x01 1
Technologies.802.15.4.Devices.Device.[0].Enabled 0x4d 0c 0x3d
Technologies.802.15.4.Devices.Device.[0].Services 0x0b 0x3b
"802.15.4_18 . . . "
Technologies.802.15.4.Devices.Device.[0].Services.[0] 0x4d 0c 0xcb
Services 0x4d 17 0x75 Services.Service.[0] 0x4b 0b 0x13 "wifi_18b43
. . . " Services.Service.[0].ID 0x4b 0d 0x14 "998-3 Alp . . . "
Services.Service.[0].Name 0x4c 0f 0x28 3939382d . . .
Services.Service.[0].SSID 0x45 10 0x02 2462
Services.Service.[0].Frequency 0x40 11 0x01 1
Services.Service.[0].AutoConnect 0x4012 0x01 1
Services.Service.[0].Favorite 0x4d 02 0x0d
Services.Service.[0].Network 0x4d 03 0x0a
Services.Service.[0].Network.IPv4 0x4d 14 0x07
Services.Service.[0].Network.IPv4.DHCP 0x45 15 0x04 0x0a02001e
Services.Service.[0].Network.IPv4.LastAddress 0x4d 17 0x50
Services.Service.[1] 0x4b 0b 0x1a "802.15.4_18 . . . "
Services.Service.[1].ID 0x4c 0d 0x10 "998-3 Alp . . . "
Services.Service.[1].Name 0x4c 0f 0x10 3939382d . . .
Services.Service.[1].EPANID 0x45 10 0x02 2412
Services.Service.[1].Frequency 0x40 11 0x01 1
Services.Service.[1].AutoConnect 0x4012 0x01 1
Services.Service.[1].Favorite
[0180] The TLV format enables reference of properties that may also
be enumerated with XML, but does so with a smaller storage size.
For example, Table 7 illustrates a comparison of data sizes of the
XML Property List, a corresponding binary property list, and the
TLV format.
TABLE-US-00009 TABLE 7 Comparison of the sizes of property list
data sizes. List Type Size in Bytes Percentage of XML Size XML
2,199 -- Binary 730 -66.8% TLV 450 -79.5%
[0181] By reducing the amount of data used to transfer data, the
TLV format enables the fabric of devices to transfer data to and/or
from devices having short duty cycles due to limited power (e.g.,
battery supplied devices). In other words, the TLV format allows
flexibility of transmission while increasing compactness of the
data to be transmitted.
[0182] Although the foregoing comparison of data types details how
the TLV format may correspond to XML format, similar corresponding
features are present when comparing the TLV format to the JSON
format mentioned above. In any case, to ensure that all devices
disposed within the smart-home environment 30 are capable of
communicating with each other and to ensure that the
cloud-computing system 64 may analyze the data received from each
device in the smart-home environment 30, the cloud-computing system
(e.g., remote server 142) may include a data conversion component
that translates TLV-format data into JSON-format data that may be
stored in appropriate buckets of information within the storage
element 158.
TLV-JSON Conversion System
[0183] With the foregoing discussions regarding the JSON-based
communication protocol and the TLV-based communication protocol in
mind, FIG. 15 illustrates a detailed view of the cloud-computing
system 64 depicted in FIG. 5 with components that enable the
cloud-computing system 64 to translate TLV-format data into
JSON-format data. Generally, when a device, such as the thermostat
46, send an update to the cloud-computing system 64, the device may
send data in the JSON-format discussed above. As such, the
JSON-format data may identify a particular bucket in the database
134 and a new value to update the identified bucket of the database
134. As a result, the cloud-computing system 64 may store data
received from various devices in an organized fashion, such that
the stored data may be easily retrieved, analyzed, processed, and
the like.
[0184] Although certain devices, such as the thermostat 46, may
communicate with the cloud-computing device 64 using JSON-format
data, other devices, such as the hazard detector 50, that may be
part of a fabric of devices may communicate using the TLV-format
data described above. As such, to update the database 134, which
may be a JSON database, the cloud-computing system 64 may translate
the received TLV-format data into an equivalent JSON-format data
and update a corresponding bucket in the database 134 using the
equivalent JSON-format data. As a result, the database 134 may be
accurately updated to include a status or state of each type of
JSON-enabled device and TLV-enabled device.
[0185] As mentioned above, the TLV-format data may have a
one-to-one mapping to a corresponding JSON-format data. In one
embodiment, this one-to-one mapping may be preserved in a
translation dictionary. The translation dictionary may initially
generated by identifying TLV-format data that corresponds to
existing JSON-format data provided by devices such as the
thermostat 46, the portable electronic device 66, and the like. The
identified TLV-format data and JSON-format data pair may be stored
in the translation dictionary. In one embodiment, the translation
dictionary may include a one-to-one mapping for each tag of the
TLV-format data and a corresponding bucket key and bucket
identifier associated with an equivalent JSON-format data. The
translation dictionary may also include a one-to-one mapping for
each value of the TLV-format data and a corresponding bucket value
associated with an equivalent JSON-format data.
[0186] Referring now to FIG. 15, to perform the translation
operations discussed above, the cloud-computing system 64 may
include a JSON component 232, a TLV component 234, a data
conversion component 236, and a translation dictionary 238. The
JSON component 232 and the TLV component 234 may be software or
hardware components that receive and send JSON-format data and
TLV-format data, respectively.
[0187] In certain embodiments, the thermostat 46 and the portable
electronic device 66 may communicate with the cloud-computing
system 64 via the JSON component 232. That is, the thermostat 46
and the portable electronic device 66 may transmit and receive data
in the JSON format and the cloud-computing system 64 may transmit
and receive JSON-format data via the JSON component 32. As such,
each part of the data transmitted or received by the thermostat 46
and the portable electronic device 66 may include information that
may be associated with some bucket. When the cloud-computing system
64 receives the JSON-format data, the cloud-computing system 64 may
store the received data in a corresponding bucket in the database
134, which may correspond to the storage element 158 described
above. As such, the database 134 may include buckets of information
based on the JSON-format data received from each JSON-enabled
device in the smart-home environment.
[0188] In addition to receiving the JSON-format data, the
cloud-computing system 64 may transmit or receive TLV-format data
to or from, for example, the hazard detector 50, which may
communicate using TLV-format data. In this case, the
cloud-computing system 64 may employ the TLV component 234 to
receive and transmit TLV-format data from and to the hazard
detector 50.
[0189] Since the database 134 may store information related to all
of the devices in the smart-home environment 30, the
cloud-computing system 64 may employ the data conversion component
236 to convert or translate the TLV-format data received via the
TLV component 234 into corresponding JSON-format data. Once
translated, the corresponding JSON-format data may be used to
update a corresponding bucket in the database 134.
[0190] With this in mind, FIG. 16 illustrates a flow chart of a
method 250 that the data conversion component 236 may employ to
translate TLV-format data received from various devices in the
smart-home environment 30 into JSON-format data. Although the
method 250 illustrates a particular order in which the blocks may
be performed, it should be noted that the method 250 may be
performed in any suitable manner and is not limited to the order
presented herein.
[0191] At block 252, the data conversion component 236 may receive
TLV-format data from one or more devices in the smart-home
environment 30. Although the method 250 is described herein with
reference to the smart-home environment 30, it should be understood
that the method 250 may be employed with data received from any
type of device within or outside the smart-home environment 30.
[0192] Upon receiving the TLV-format data, at block 254, the data
conversion component 236 may identify a profile Id using the tag
field 222 of the TLV-format data. In certain embodiments, the data
conversion component 236 may also receive a vendor Id and a tag
number field from the tag field 22 of the TLV-format data. In
certain embodiments, the data conversion component 236 may infer
the vendor Id and the profile Id based on the tag number. The
vendor Id may indicate a vendor that manufactured the respective
device that transmitted the TLV-format data and the profile Id may
indicate a type of the device (e.g., hazard detector 50).
[0193] In any case, after determining the profile Id for the
respective device, at block 256, the data conversion component 236
may determine a bucket key using the profile Id and the translation
dictionary 238. As mentioned above, the translation dictionary 238
may include a mapping between the TLV-format data and an equivalent
JSON-format data. In one embodiment, the translation dictionary 238
may include mappings for various possible profile Ids and
corresponding bucket keys associated therewith. The bucket key may
correspond to a label for a particular bucket that may be part of
the database 134.
[0194] By way of example, the tag field 222 of the TLV-format data
may include a hexadecimal value: "0x123" that corresponds to the
profile Id. The data conversion component 236 may then use the
translation dictionary 238 to determine a bucket key that
corresponds to the profile Id received via the tag field 222 of the
TLV-format data.
[0195] At block 258, the data conversion component 236 may
determine a bucket identifier using an instance Id specified in the
tag field 222 and the translation dictionary 238. As such, the data
conversion component 236 may use the translation dictionary 238 to
determine an equivalent bucket identifier that corresponds to the
instance Id. The bucket identifier may be used to determine a
particular instance of the bucket identified at block 254.
[0196] After identifying a particular bucket key and bucket
identifier that corresponds to the received TLV-format data, the
data conversion component 236 may, at block 260, determine a bucket
value based on a value provided in the value field 226 of the
TLV-format data. In one embodiment, the value in the value field
226 may directly correspond to a value that may be used to update
the identified bucket. For example, if the hazard detector 50
provides TLV-format data that includes a 1 to indicate that a
hazard is present and a 0 to indicate that a hazard is not present,
the data conversion component 236 may then use the same 1 or 0 to
update the identified bucket. That is, the data conversion
component 236 may use the value of the value field 226 to update a
value of the identified bucket.
[0197] In certain embodiments, however, certain values may not
properly translate based on the value of the value field 226. For
example, the TLV-format data associated with occupancy information
(e.g., whether a living being is present in the smart-home
environment 30) may include values 1, 0, or -1, which may represent
occupied, not occupied, and unknown, respectively. Here, the
negative value, -1, may not have an equivalent value representation
in the JSON-format data. That is, JSON-format data may not include
negative values. In this case, the translation dictionary 238 may
include a mapping for certain values that may be part of the
TLV-format data but may not have an equivalent JSON-format
representation. For instance, the translation dictionary 238 may
include a mapping that associates the occupied state, 1, in the
TLV-format data with a two-bit value 01, a mapping that associates
the unoccupied state, 0, in the TLV-format data with a two-bit
value 00, and a mapping that associates the unknown occupied state,
-1, in the TLV-format data with a two-bit value 11. The mapped
two-bit values may thus be used to update appropriate buckets in
the database 134.
[0198] Keeping the foregoing in mind, the translation dictionary
238 may include custom mappings between values that may be
represented in the TLV-format data and corresponding values in the
JSON-format data. In certain embodiments, the translation
dictionary 238 may be updated as values in the TLV-format data are
identified as not having equivalent JSON-format data
representations. In the same manner, the translation dictionary 238
may be updated as new profile Ids, instance Ids, and the like
associated with the tag field 222 is identified. In one embodiment,
the translation dictionary 238 may be updated manually. That is,
the translation dictionary 238 may be updated by new manufacturers
(e.g., third-party devices) as new entries for the tag field 222 or
the value field 226 are created for the respective new device.
[0199] Although JSON-format data includes some equivalent
representation for most types of values specified in the TLV-format
data, JSON-format data is not capable of representing a byte string
or byte array, while the TLV-format data may include data in the
value field 226 as a byte string or byte array. As such, if the
TLV-format data received via the TLV component 234 is expected to
include a packed binary data such as a byte string, the translation
dictionary 238 may include a custom translation or mapping that may
be used to determine an equivalent bucket value that may be used to
encode the JSON-format data. In one embodiment, when receiving a
byte string of the TLV-format data, if the translation dictionary
238 does not provide a respective mapping for the respective byte
string, the data conversion component 236 may just receive the bye
stream before encoding the translated portions of the TLV-format
data with corresponding JSON-format data. In another embodiment,
the cloud-computing system 64 may receive each portion of the byte
string and update the corresponding bucket using an anonymous tag
for each portion of the byte string. The anonymous tag may denote
that the received data is part of a byte string and thus may be
associated with an appropriate byte string.
[0200] Referring back to FIG. 16, at block 262, the data conversion
component 236 may encode the bucket key, the bucket identifier, and
bucket value determined from blocks 254, 258, and 260 as
JSON-format data. At block 264, the data conversion component 236
may then store the JSON-format data in an appropriate location of
the database 134. In certain embodiments, the data conversion
component 236 may provide the JSON-format data to the JSON
component 232, which may then properly update respective buckets in
the database 134 based on the JSON-format data. In another
embodiment, the data conversion component 236 may identify the
bucket that corresponds to the JSON-format data and update the
respective buckets accordingly. In yet another embodiment, the data
conversion component 236 may update the database 134 while
determining the bucket key, the bucket identifier, and bucket value
at blocks 254, 258, and 260.
[0201] After the database 134 and the respective buckets of the
database 134 are updated, the cloud-computing system 64 may have
access to current data regarding all of the devices of the
smart-home environment 30 in one interpretable format. As such, the
cloud-computing system 64 may effectively manage the operations of
each of the devices in the smart-home environment 30 based on the
conditions of each respective device. Moreover, subscription
services provided by the cloud-computing system 64 may perform
their respective operations based on up to date data regarding each
of the devices in the smart-home environment 30. Additionally, when
analyzing the aggregated data related to the smart-home environment
30, the cloud-computing system 64 may perform analysis operations
using various data analysis tools without performing any further
data translation operations. As a result, the cloud-computing
system 64 may efficiently analyze the data of the database 134 and
efficiently manage the respective operations of the devices of the
smart-home environment 30.
[0202] After analyzing the data of the database 134, the
cloud-computing system 64 may then send commands to various devices
of the smart-home environment 60 based on the results of the
analysis. In certain embodiments, the cloud-computing system 64 may
send JSON-format data or TLV-format data to the respective devices.
As such, if the cloud-computing system 64 attempts to update a
device that communicates using TLV-format data with data from the
database 134, the cloud-computing system 64 may translate the
JSON-format data from the database 134 into TLV-format data using
the translation dictionary 238. The cloud-computing system 64 may
then send the TLV-format data to the respective device, such that
the respective device may update its respective data.
[0203] Although the method 250 of FIG. 16 is described as being
performed by the cloud-computing system 64, it should be noted that
the method 250 may be performed by other devices that also include
one or more processors. For example, the methods described herein
may also be performed by any type of device 10 that may be employed
in the smart-home environment 30 or the like.
[0204] The specific embodiments described above have been shown by
way of example, and it should be understood that these embodiments
may be susceptible to various modifications and alternative forms.
It should be further understood that the claims are not intended to
be limited to the particular forms disclosed, but rather to cover
all modifications, equivalents, and alternatives falling within the
spirit and scope of this disclosure.
* * * * *
References