U.S. patent application number 14/479136 was filed with the patent office on 2014-12-25 for system and method for waste managment.
The applicant listed for this patent is Compology, Inc.. Invention is credited to Benjamin Chehebar, Jason Skylar Gates.
Application Number | 20140379588 14/479136 |
Document ID | / |
Family ID | 52111751 |
Filed Date | 2014-12-25 |
United States Patent
Application |
20140379588 |
Kind Code |
A1 |
Gates; Jason Skylar ; et
al. |
December 25, 2014 |
SYSTEM AND METHOD FOR WASTE MANAGMENT
Abstract
A method for waste management, including recording an image of
content within a waste container; extracting a set of content
parameters from the image; characterizing the content within the
waste container based on the set of content parameters; and routing
a waste removal vehicle based on the content characterization.
Inventors: |
Gates; Jason Skylar; (San
Francisco, CA) ; Chehebar; Benjamin; (San Francisco,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Compology, Inc. |
San Francisco |
CA |
US |
|
|
Family ID: |
52111751 |
Appl. No.: |
14/479136 |
Filed: |
September 5, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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14211709 |
Mar 14, 2014 |
|
|
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14479136 |
|
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|
61801021 |
Mar 15, 2013 |
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Current U.S.
Class: |
705/308 |
Current CPC
Class: |
Y02W 90/20 20150501;
G06T 2207/30232 20130101; G06Q 10/30 20130101; G06Q 10/0631
20130101; G06T 7/0008 20130101; G06T 2207/30242 20130101; H04N
7/181 20130101; Y02W 90/00 20150501 |
Class at
Publication: |
705/308 |
International
Class: |
G06Q 10/00 20060101
G06Q010/00; G06T 7/00 20060101 G06T007/00; H04N 7/18 20060101
H04N007/18 |
Claims
1. A method for waste management, comprising: for each of a
plurality of waste containers, recording a measurement of content
within the respective waste container; extracting a content
parameter for the respective content from each measurement;
determining a volume parameter for the respective content from each
measurement; determining a purity index for a material category for
each waste container, based on the respective content parameter;
selecting a subset of the plurality of waste containers for
retrieval based on the respective material purity index and volume
parameter; and routing a waste removal vehicle to retrieve content
from the selected subset of waste containers.
2. The method of claim 1, wherein the measurement comprises an
image.
3. The method of claim 2, wherein content parameter comprises a
material property measurement for the content.
4. The method of claim 3, wherein the material property measurement
comprises an optical property measurement.
5. The method of claim 1, wherein the subset of the plurality of
waste containers are selected in response to the respective volume
parameters exceeding a threshold value.
6. The method of claim 1, wherein routing the waste removal vehicle
comprises selecting the subset of waste containers to obtain a
threshold purity index for the totality of the content retrieved
from the selected subset of waste containers.
7. The method of claim 1, further comprising calculating a monetary
value for each container based on the respective material purity
index, wherein the subset of the plurality of waste containers is
selected maximize the monetary value for the retrieved content.
8. The method of claim 1, further comprising: during content
retrieval, recording a measurement of content within the waste
removal vehicle; extracting a content parameter for the content of
the waste removal vehicle; determining a purity index from the
content parameter for the material category for the waste removal
vehicle; and comparing the purity index with a preliminary purity
index, wherein the preliminary purity index is calculated from the
respective purity indices of the waste containers from which
content has been retrieved.
9. A method for waste management, comprising: recording an image of
content within a waste container; extracting a set of content
parameters from the image; characterizing the content within the
waste container based on the set of content parameters; and routing
a waste removal vehicle based on the content characterization.
10. The method of claim 9, wherein the image is recorded in
response to an occurrence of a trigger event
11. The method of claim 10, wherein the trigger event comprises
ambient light exceeding a light threshold.
12. The method of claim 9, wherein the image comprises a
stereoscopic image
13. The method of claim 9, wherein the set of content parameters
comprises brand names.
14. The method of claim 13, wherein characterizing the content
comprises determining a content index based on packaging material
information associated with the brand name.
15. The method of claim 9, wherein the content characterization
comprises a fullness percentage, comprising a volume of content
relative to a volume of the waste container.
16. The method of claim 15, further comprising calculating a
monetary value for the content, wherein the content
characterization further comprises a value of the content.
17. The method of claim 16, wherein calculating the monetary value
for the content comprises: determining a material composition of
the content based on the image; and calculating the monetary value
for the content based on market rates.
18. The method of claim 9, further comprising repeating: recording
an image of content within a waste container, extracting a set of
content parameters from the image, and characterizing the content
within the waste container based on the set of content parameters
multiple times over a period of time.
19. The method of claim 9, further comprising estimating a time at
which a content parameter of the set will exceed a threshold value,
wherein the waste removal vehicle is routed based on the estimated
time.
20. The method of claim 19, wherein the content parameter comprises
a volume of content within the waste container.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation in part of U.S.
application Ser. No. 14/211,709 filed 14 Mar. 2014, which claims
the benefit of U.S. Provisional Application No. 61/081,021, filed
15 Mar. 2013, both of which are incorporated in their entirety by
this reference.
[0002] This application claims priority to U.S. Provisional
Application No. 61/801,021 filed 15 Mar. 2014, which is
incorporated in its entirety by this reference.
TECHNICAL FIELD
[0003] This invention relates generally to the waste management
field, and more specifically to a new and useful system and method
for waste recovery and routing in the waste management field.
BRIEF DESCRIPTION OF THE FIGURES
[0004] FIG. 1 is a schematic representation of a variation of the
monitoring system.
[0005] FIG. 2 is a schematic representation of a second variation
of the monitoring system.
[0006] FIGS. 3, 4, and 5 are schematic representations of a first,
second, and third variation of waste containers including
monitoring systems, respectively.
[0007] FIGS. 6 and 7 are schematic representations of a first and
second variation of the method of recording a measurement of the
waste contained within the waste container, respectively.
[0008] FIG. 8 is a schematic representation of a method of waste
management.
[0009] FIG. 9 is a schematic representation of a monitoring system,
remote system, waste collection system, and receiving facility
performing a variation of the method.
[0010] FIG. 10 is a schematic representation of an example of a
method of waste management, including recording measurements from
waste containers A, B, and C and routing waste collection vehicles
to the waste containers based on the respective content
metrics.
[0011] FIG. 11 is a schematic representation of an example of
extracting content metric for the waste within the waste container
from a measurement using object recognition.
[0012] FIG. 12 is a schematic representation of an example of
determining the content metric for the waste within the waste
container based on a first and second measurement.
[0013] FIG. 13 is a schematic representation of an example of
performing the method at a first and second time for the waste
within a waste container between waste collections, and rerouting
the waste within the waste container in response to a change in the
respective content metric.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0014] The following description of the preferred embodiments of
the invention is not intended to limit the invention to these
preferred embodiments, but rather to enable any person skilled in
the art to make and use this invention.
1. System.
[0015] The monitoring system 100 preferably includes a content
sensor 200, communication system 300, and housing 400, and can
additionally include a measurement trigger detection mechanism or
any other suitable component. The monitoring system 100 functions
to collect information about the contents of the waste container.
The contents can be solids (e.g., recycling, trash, compost, etc.),
liquids (e.g., cooking oil, motor oil, etc.), gasses, industrial
waste, manufacturing waste, or any other suitable material. More
preferably, the monitoring system 100 records the measurements 30
of the contents 10 of the waste container 20, but can alternatively
collect any other suitable information about the waste container
20.
[0016] The collected information can subsequently be used to
increase the sorting efficiency at receiving facilities (e.g.,
recycling facilities, composting facilities, landfills, etc.),
increase the accuracy of monetary charges for waste collection,
receiving and processing, increase the monetary value of collected
waste (e.g., by picking up containers having similar content
purity), optimize the collection routes based on waste volume,
value, mileage, or any other suitable parameter, to more accurately
credit facilities' customers for valuable waste content, to create
a market around purchasing the waste contained in a waste container
(e.g., through brokering, bidding, etc.), to determine an economic
parameter (e.g., health) of a company or economy, to tailor
marketing and/or determine the efficacy of an advertising campaign
(e.g., wherein brand names can be recognized in the waste), to
determine an ideal time to pick up the waste based on the rate of
content increase and predicted weather, to leverage waste
containers as a temporary storage location for low-value or other
waste, or used in any other suitable manner.
[0017] The monitoring system 100 is preferably configured to attach
to the interior of the waste container, but can alternatively be
configured to attach to the exterior, edge, or any other suitable
portion of the waste container. The monitoring system 100 is
preferably configured or arranged to monitor all or a portion of
the waste container interior, but can alternatively be configured
or arranged to monitor the contents entering the waste container,
the contents about to enter the waste container (e.g., contents
that have not broken the plane of the waste container opening), or
monitor any other suitable portion of the waste container
vicinity.
[0018] The content sensor 200 of the monitoring system 100
functions to monitor the content of the waste container by
recording measurements 30 of the waste 10. The content sensor 200
is preferably an optical sensor configured to record images, but
can alternatively be an audio sensor (e.g., microphone), an
electromagnetic sensor (e.g., a magnet or coil, etc.), a near-field
communication sensor (e.g. an RFID sensor, NFC sensor, etc.), a
weight sensor, a temperature sensor, a chemical compound sensor,
metal detector, or any other suitable sensor. Examples of optical
sensors include a monocular camera, stereocamera, multi-lens or
multi-view camera, color camera (e.g., a RGB camera) such as a
charge coupled device (CCD) or a camera including a CMOS sensor,
grayscale camera, multispectral camera (narrow band or wide band),
hyperspectral camera, ultraspectral camera, spectral camera,
spectrometer, time of flight camera, high-, standard-, or
low-dynamic range cameras, range imaging system (e.g., LIDAR
system), active light system (e.g., wherein a light, such as an IR
LED, is pulsed and directed at the subject and the reflectance
difference measured by a sensor, such as an IR sensor), thermal
sensor, infra-red imaging sensor, projected light system, full
spectrum sensor, high dynamic range sensor, or any other suitable
imaging system. The optical sensor is preferably configured to
capture a 2-dimensional or 3-dimensional image, but can
alternatively capture any a measurement having any other suitable
dimension. The image is preferably single, multi-pixel,
time-averaged or sum total measurement of the intensity of a signal
emitted or reflected by objects within a field of view, but can
alternatively be a video (e.g., a set of images or frames), or any
other suitable measurement. The image preferably has a resolution
(e.g., cycles per millimeter, line pairs per millimeter, lines of
resolution, contrast vs. cycles/mm, modulus of the OTF, or any
other suitable measure) capable of resolving a 1 cm.sup.3 object at
a sensor distance of at least 10 feet from the object, but can
alternatively have a higher or lower resolution. Alternatively, the
content sensor 200 can record data that requires two or more
measurements, is a single pixel, is location independent, or has
any other suitable parameter. The monitoring system 100 can include
one or more content sensors of the same or different type.
[0019] The content sensor 200 of the monitoring system 100 can
additionally be coupled with one or more emitters that are
configured to emit electromagnetic signals, audio signals,
compounds, or any other suitable interrogator that the content
sensor 200 is configured to measure. Alternatively, the content
sensor 200 can measure signals from the ambient environment.
Examples of content sensor-emitter pairs include LIDAR systems,
time-of-flight systems, ultrasound systems, radar systems, X-ray
systems, or any other suitable system. When the content system
includes an emitter 220, the system can additionally include a
reference sensor that measures the ambient environment signals,
wherein the content sensor measurement can be corrected by the
reference sensor measurement.
[0020] The content sensor 200 of the monitoring system 100 can
additionally include a lens that functions to adjust the optical
properties of the incident signal on the sensor. For example, the
optical sensor can include a fish-eye lens to broaden the area
monitored by the optical sensor, wherein the resultant distortion
is known and can be adjusted for during image processing. However,
the lens can be a wavelength filter, polarizing filter, or any
other suitable lens. The content sensor 200 can alternatively
include a physical or digital filter, such as a noise filter that
corrects for interferences in the measurement.
[0021] The communication system 300 of the monitoring system 100
functions to communicate data from the monitoring system 100 to a
second system. The data can be measurements from the content sensor
200 or any other suitable component, processed measurements,
instructions, pickup requests, or any other suitable data. The
second system can be a device, server system, or any other suitable
computing system. The second system can be remote or wired to the
communication system 300. Examples of the second system include a
mobile device (e.g., smartphone, tablet, computer), server system,
or any other suitable computing system. The communication system
300 can be a wireless or wired communication system. The
communication system 300 can be a cellular, WiFi, Zigbee, Z-Wave,
near-field communication system (e.g., Bluetooth, RF, NFC, etc.),
Ethernet, powerline communication, or any other suitable
communication system. The communication system 300 is preferably
operable in a standby or off mode, wherein the communication system
300 consumes power at a rate less than a threshold rate, and an on
or communication mode, wherein the communication system 300
consumes power at a rate required to communicate data. However, the
communication system 300 can be operable in any other suitable
mode.
[0022] The housing 400 of the monitoring system 100 functions to
mechanically protect the monitoring system components, including
the content sensor 200 and communication system 300. The housing
400 preferably forms a liquid-impermeable seal about the monitoring
system components, but can alternatively be hermetic,
fluid-impermeable, gas-impermeable, or have any other suitable
characteristic. The housing 400 can additionally include vents,
selectively permeable membranes or orifices (e.g., include a
Gore.TM. membrane, etc.), or any other suitable component that
permits selective venting or removal of undesirable substances
(e.g., fluids) from the housing interior. The housing 400
preferably additionally includes a mounting mechanism that
functions to removably or semi-permanently mount to the waste
container. The housing 400 preferably includes a back casing 420
and a front casing 440. The monitoring system components are
preferably mounted or otherwise supported by the back casing. The
back casing can additionally include the mounting mechanism (e.g.,
along a broad face). The front casing can be translucent,
transparent, function as the lens or filter, or have any other
suitable optical property. The front casing is preferably
transparent or translucent to the signal measured by the content
sensor 200, but can alternatively be substantially opaque. The
casing can additionally include a gasket or other suitable
interface between the front and back casing. The casing can
additionally include a mask or other component configured to absorb
light emitted by an emitter 200 that is reflected by the front
casing, waste object, or any other suitable surface. The mask can
absorb light along a predetermined set of wavelengths (e.g., be
black), textured, or have any other suitable optical feature.
[0023] The monitoring system 100 can additionally include a
measurement trigger detection mechanism or auxiliary sensor 500
that functions to determine a trigger event that triggers content
sensor measurement of the waste container contents. The measurement
trigger detection mechanism can be an ambient light sensor (e.g.,
wherein the ambient light within the waste container changes each
time the lid is lifted), laser beam break sensor (e.g., wherein
objects entering the container will break a laser beam directed
across the container opening), accelerometer or gyroscope (e.g.,
wherein lid opening or object landing within the container will
shake the monitoring system 100 mounted to the container), timer or
clock, or be any other suitable detection mechanism. However, the
monitoring system 100 can include a location sensor (e.g., a GPS
system, cell tower triangulation system, etc.) or any other
suitable sensor. The measurement trigger detection mechanism is
preferably oriented at a non-zero angle (e.g., 90 degrees) relative
to the content sensor line of view (e.g., axis perpendicular to the
sensor), but can alternatively be arranged with an active area
parallel to the sensor area or be arranged in any other suitable
configuration.
[0024] The monitoring system 100 can additionally include a
processor 600 that functions to receive measurements from the
content sensor 200 and auxiliary sensors (if included) and control
communication system operation to send the measurements or
information derived from the measurements to the second system. The
processor 600 can additionally function to process the measurements
(e.g., compress the measurements), perform any suitable portion of
the method, or perform any other suitable functionality.
[0025] The monitoring system 100 can additionally include a power
source 700 or be connected to a remote power source (e.g., a power
grid). The power source 700 is preferably a battery, more
preferably a secondary battery, but can alternatively be a fuel
cell with a fuel source (e.g., metal hydride) or any other suitable
power source. The secondary battery can have a lithium phosphate
chemistry, lithium ion polymer chemistry, lithium ion chemistry,
nickel metal hydride chemistry, lead acid chemistry, nickel cadmium
chemistry, metal hydride chemistry, nickel manganese cobalt
chemistry, magnesium chemistry, or any other suitable chemistry.
The battery is preferably electrically connected to the powered
monitoring system components, wherein the processor 600 preferably
controls power provision (e.g., through component operation mode
control), but power provision and/or battery management can
alternatively be performed by any other suitable component.
[0026] The monitoring system 100 can additionally be used with or
include a measurement processing module and/or a routing module.
The modules can be executed on the processor 600 of the monitoring
system 100, on a remote system 60 (e.g., a remote server), or on
any other suitable computing system. The measurement processing
module functions to process the measurements recorded by the
content sensor 200 and/or auxiliary sensors 500 to extract a
content parameter 12. The content parameter 12 is subsequently used
to determine content metrics 14, which classify the contents
(waste) of the respective waste container. For example, the content
parameter can be used to determine the waste material purity or
composition, value, form factor composition, brand inclusion,
volume, or any other suitable content characterization.
[0027] The content characterization and/or content parameter values
can subsequently be used to determine the waste containers that
should be emptied (e.g., the waste that should be collected) by a
given waste collection vehicle targeted to end at a predetermined,
selected, or otherwise determined endpoint. For example, the
routing module can select waste containers having a threshold
recyclables purity index (e.g., containers containing at least 55%
recyclables) for collection by a recycling truck that is assigned
to deliver the collected waste to a recycling facility that pays
for waste having 55% or more recyclable content. In a second
example, the routing module can select waste containers for
collection by the recycling truck assigned to deliver the collected
waste to a recycling facility to meet a threshold recyclables
purity index value for the entirety of the waste anticipated to be
collected. In a specific example, if the threshold recyclables
purity index value is 55%, the routing module can route the vehicle
to collect waste from a first waste container containing content
having a 45% purity index and from a second waste container
containing content having a 65% purity index. The routing module
can additionally function to determine the optimal route (e.g.,
least expensive, fastest, most cost-effective, etc.) to collect
waste from the selected waste containers. However, the monitoring
system 100 can be used with any other suitable data processing
modules.
[0028] The monitoring system 100 is preferably utilized with a
waste container 20. The waste container 20 functions to receive and
contain waste 10. The waste container 20 can additionally function
to supply waste 10 (e.g., when emptied). The waste container 20 is
preferably a dumpster, bin, or other container, but can
alternatively be the hopper 52, bed, or other suitable portion of
the waste collection vehicle. The waste container 20 is preferably
substantially rigid, and preferably includes a body that defines a
waste-retaining cavity 24 having an open end and a lid 24 that
seals the open end. The waste container 20 can be rectangular or
have any other suitable configuration. In one variation, the waste
container interior can be colored a reference color or include a
symbol, line, or other reference indicator, such that the image
analysis system can use the reference indicator as a reference
point (e.g., calibration color, volume threshold level, position
correction reference, etc.). Alternatively, the waste container
interior can have a color that absorbs interfering signals,
amplifies desired signals, or otherwise influences the content
measurement. The waste container is preferably made of metal, more
preferably non-ferrous metal but alternatively any other suitable
metal, but can alternatively be made of polymer or any other
suitable material. The waste container material preferably does not
interfere with the content measurement, but can alternatively be
made of material that interferes with the content measurement,
wherein the noise introduced by the waste container material is
preferably known, measured, or otherwise determined and corrected
for during measurement processing. The waste container preferably
includes a unique identifier stored by the monitoring system 100 or
otherwise determined by the monitoring system 100, but can be
otherwise identified. The waste container identifier can be a
geographic location (e.g., GPS coordinate, latitude/longitude
coordinate, etc.), but can alternatively be an RFID identifier,
barcode identifier, or any other suitable identifier.
[0029] The monitoring system 100 is preferably mounted to the waste
container 20 proximal an edge of the waste container opening, more
preferably proximal or in a corner of the waste container proximal
the opening, but can alternatively be mounted along a wall of the
container, the floor of the container, the lid of the container, or
along any other suitable portion of the container. Alternatively,
the monitoring system 100 can be mounted to a mounting point
external the container. One or more monitoring systems can be used
for a single waste container. When multiple monitoring systems are
used, the monitoring systems are preferably directed at different
angles or fields of view. In one example, a first monitoring system
can be arranged in a corner of the container proximal the edge, a
second monitoring system can be arranged in a second corner
proximal the edge adjacent the first corner, and a third monitoring
system can be arranged on the interior surface of the lid. However,
any suitable number of monitoring systems can be arranged in any
other suitable set of positions.
[0030] The waste 10 (rubbish, refuse, content, etc.) contained
within the waste container 20 can be solid, fluid, liquid, gas, or
have any other suitable form factor. Examples of waste include
municipal solid waste (household trash/refuse), hazardous waste,
wastewater (such as sewage, which contains bodily wastes, or
surface runoff), radioactive waste, or any other suitable waste.
The waste can be categorized by type (e.g., recyclable,
compostable, landfill, etc.), material (e.g., metal, organic,
plastic, glass, etc.), form factor (e.g., bottle, bag, etc.), or
any other suitable category or subset thereof.
[0031] The monitoring system 100 can additionally be used with a
waste collection vehicle 50. The waste collection vehicle 50 can
belong to a third party waste removal entity, a receiving facility,
a retail entity, or any other suitable entity. The waste collection
vehicle functions to receive the waste from the waste containers.
The waste collection vehicle 50 can include a transportation
mechanism, a hopper, and a loading mechanism, but can alternatively
include any suitable subset of the above (e.g., wherein the waste
collection vehicle 50 is manually loaded) or any other suitable
component. The transportation mechanism can include the drive train
and/or transmission of a vehicle (e.g., the motor and wheels of a
vehicle), but can alternatively include any other suitable
transportation mechanism. The transportation mechanism is
preferably manually controlled (e.g., by a driver), but can
alternatively be automatically controlled (e.g., driverless),
wherein the transportation mechanism can automatically drive the
waste collection vehicle along the route specified by the method,
or along any other suitable route.
[0032] The hopper 52 functions to receive and transiently retain
the waste from the waste container. The hopper 52 preferably
includes a body defining a waste containment volume, and can
additionally include a lid. The hopper 52 is preferably made of
metal, but can alternatively be made of plastic or any other
suitable material. The hopper material preferably does not
interfere with the content measurement, but can alternatively be
made of material that interferes with the content measurement,
wherein the noise introduced by the hopper material is preferably
known, measured, or otherwise determined and corrected for during
measurement processing.
[0033] The loading mechanism preferably functions to transiently
couple to the waste container, align the waste container with all
or a portion of the hopper opening, empty the waste container into
the hopper, place the waste container on the support surface (e.g.,
the ground), and release the waste container. The loading mechanism
can be a pneumatic arm, magnetic arm, or any other suitable loading
mechanism.
[0034] The waste collection vehicle 50 functions to transport the
waste from the waste container(s) to an endpoint. The endpoint is
preferably a receiving facility 40 (e.g., waste processing plant),
but can alternatively be a second waste container or be any other
suitable endpoint. The endpoints can be content-type specific,
content-material specific, content-form factor specific, or have
any other suitable characteristics. Alternatively, the endpoints
can prefer certain waste categories but accept other, non-preferred
waste categories. Alternatively, the endpoints can be waste
category agnostic. Examples of endpoints include recycling plants
(e.g., metal recycling facilities, glass recycling facilities,
plastic recycling facilities, etc.), composting plants, landfills,
rendering plants, refineries, manufacturing facilities (e.g.,
wherein the material functions as an input to a manufacturing
process), collection facilities, or any other suitable endpoint.
The endpoints can additionally publish or otherwise provide a
monetary value or cost per content parameter, which can be
transmitted to a waste container selection module, the waste
containers, an entity associated with the waste collection vehicle,
or any other suitable system. An example of monetary value assigned
to a content parameter includes a monetary value for a purity index
range (e.g., the facility will pay $10 for each pound of waste
having a 60%-80% purity index for glass). An example of monetary
cost assigned to a content parameter includes a monetary cost for a
purity index range (e.g., the facility will charge $20 to receive
each pound of waste having a 10-30% purity index for glass).
2. Method.
[0035] The method for waste management includes recording a
measurement of content within a waste container S100, extracting a
set of content parameters from the measurement S200, characterizing
the content within the waste container based on the set of content
parameters S300, and routing a waste collection vehicle based on
the content characterization S400. The method functions to monitor
the contents of waste containers in near-real time, at a
predetermined frequency, or at any other suitable frequency. The
method additionally functions to identify the contents of the waste
container, or a parameter thereof. The method additionally
functions to identify waste containers for waste removal based on
the respective contents and/or identify when to remove waste from
the identified waste containers based on the current and
anticipated contents. The method additionally functions to select a
route and/or endpoint for a waste collection vehicle based on the
contents of the identified waste containers. The method is
preferably repeated for multiple waste containers over prolonged
times, but can alternatively be performed once, performed for a
single waste container, or performed at any other suitable
frequency. The method is preferably repeated at a predetermined
frequency, but can alternatively be performed in response to
trigger events or at any other suitable frequency. The method is
preferably automatically performed by the system, but can
alternatively be performed manually, semi-manually, or otherwise
performed.
[0036] In one example, the method selects the waste containers for
waste removal to maximize the value of the waste collected by a
waste collection vehicle. In another example, the method selects
the waste containers for waste removal to maximize the purity of
the waste collected by a waste collection vehicle. In another
example, the method selects the endpoint (e.g., landfill, recycling
plant, composting plant, etc.) based on the contents of the
collected waste. The method can additionally function to collect
information about the contents of a set of waste containers and
determine economic parameters (e.g., the health of an economy or
entity associated with the set of containers, etc.) based on the
information. In a specific example, the method can be used to
inform regulators of economic waste parameters, such that the
regulators can tailor outreach to influence consumer actions (e.g.,
increase recycling and/or composing rates). In a second specific
example, the method can function to provide information to
receiving facilities to predict future facility demand in real- or
near-real time, such that the facility can dynamically adjust their
resources (e.g., personnel, number of plants running, etc.) to meet
the future demand. In a third example, the method can function to
provide information to waste generators (e.g., consumers, users,
etc.) about their respective waste profile, such that the waste
generators can adjust their activity to achieve
generator-determined or otherwise determined waste goals (e.g.,
reduce contamination in waste streams, increase cardboard
compaction, etc.). The information can additionally be utilized to
provide rebates to the waste generators, or used in any other
suitable manner.
[0037] The method is preferably performed by the system 100
described above, but can alternatively be performed by a system
connected to the monitoring system 100, or by any other suitable
system. When the measurements, content parameters, content indices,
or other data are processed by a secondary system 60, the
monitoring system 100 preferably sends the measurements to the
secondary system 60. The measurements, content parameters, content
indices, or any other suitable information can be sent by the
monitoring system 100 to the secondary system at a predetermined
frequency, in response to measurement recordation, in response to
recordation of a threshold number of measurements, in response to
request receipt, or in response to any other suitable sending
event. The communication system 300 is preferably operated in the
communication mode to send the data, then switched to a standby,
shut off, or power saving mode. This can function to minimize power
utilization. Alternatively, the communication system 300 can remain
in the communication mode. Alternatively, the receiver can of the
communication system 300 can remain in the communication mode, be
switched to the communication mode at a predetermined frequency, or
be switched to the standby mode, while the transmitter can be
switched to the standby mode, be switched to the communication mode
at a predetermined frequency, or remain in the communication mode.
However, the communication system 300 can be operated in any other
suitable manner.
[0038] Recording a measurement of content (content measurement)
within a waste container S100 functions to record a measurement
indicative of a content parameter of interest. The content
measurement 30 is preferably recorded by the content sensor(s), but
can alternatively be recorded by any other suitable sensor. The
content measurement is preferably of at least a portion of the
waste container interior, more preferably a majority of the waste
container interior (e.g., 100%, 90% of the waste container volume,
etc.) but can alternatively be a measurement of the waste container
opening, a measurement of an area proximal the waste container
opening that is exterior or interior the waste container, or
measure any other suitable area or volume relative to the waste
container. The content measurement is preferably the output of any
of the content sensors or other sensors disclosed above, but can
alternatively be the output of any other suitable sensor or system.
Recording the content measurement can additionally include emitting
a signal, wherein the reflected portions of the signal are recorded
by the measurement. However, the content measurement can record
signals emitted by an external source, the waste, or signals from
any other suitable source.
[0039] The content measurement is preferably automatically
recorded, but can alternatively be manually recorded (e.g., by a
user) or otherwise recorded. The content measurement is preferably
recorded in response to the occurrence of a trigger event, wherein
the trigger event preferably occurs multiple times between
collection events (e.g., wherein the container is substantially
emptied of waste), but can alternatively occur once. The content
measurement can be recorded during content deposition into the
waste container (e.g., as the waste falls into the container),
before the content is deposited into the waste container, after the
content is deposited into the waste container, or measured at any
other suitable time. The trigger event can be indicative of lid
actuation, but can alternatively be indicative of waste deposition
into the waste container, indicative of any other suitable waste
event, the meeting of a time duration (e.g., wherein the
measurement is recorded at a predetermined frequency), receipt of a
measurement request, or any other suitable trigger event. The
trigger event indicative of lid actuation can include an acoustic
intensity change beyond an acoustic threshold or acoustic
difference threshold (e.g., increase in ambient noise), light
intensity change beyond a light threshold or light difference
threshold (e.g., increase in ambient light within the container),
vibration beyond a vibration threshold (e.g., increase in the
system vibration), acceleration beyond an acceleration threshold
(e.g., wherein the sensor can be attached to the lid), weight
change, actuation of a mechanical indicator (e.g., release of a
lever actuated by a closed lid, etc.), or be any other suitable
event. The trigger event indicative of waste deposition can include
detecting a break in a beam of light directed across the container
opening or across any other suitable containment volume
cross-section. However, the trigger event can include the
satisfaction of any other suitable condition. The content sensor
200 is preferably switched to operation in a recording or capturing
mode in response to the trigger event, then switched to a standby,
shut off, or power saving mode after content measurement
recordation. Alternatively, the content sensor 200 can be operated
in the capturing mode for a predetermined period of time,
perpetually operated in the capturing mode, or operated in any
other suitable manner.
[0040] Recording the content measurement S100 can additionally
include selecting the measurement to be recorded. This can be used
when the monitoring system 100 includes multiple sensors. The
content measurement can be selected based on a secondary
measurement (e.g., an ambient environment measurement, the trigger
event measurement, etc.), but can alternatively be randomly
selected or selected in any other suitable manner. In one example,
a first content measurement (e.g., a mid-infrared image for
measuring moisture content) is selected in response to a content
weight increase beyond a weight threshold, and a second content
measurement (e.g., a full color monoview image) is selected in
response to a content weight increase below the weight threshold.
The weight threshold can be the same as or different from the
weight threshold used to determine occurrence of the trigger event.
However, the content measurement can be selected in any other
suitable manner. Alternatively, the set of content measurements
that are recorded can be fixed (e.g., based on the sensors that are
provided). In one variation wherein the monitoring system 100
includes multiple sensors, the sensors can record content
measurements simultaneously (e.g., near-simultaneously),
sequentially, or in any other suitable order.
[0041] In a first variation, the content measurement is an image.
The image can be a single frame, multi-frame (e.g., stereogram),
full-color (e.g., along all or a plurality of continuous
wavelengths in the visible range), multispectral (e.g., along a
range of wavelengths in the visible range), hyperspectral (e.g.,
along a set of wavelength ranges in the visible range),
full-spectral, or be any other suitable image. The image is
preferably two-dimensional, but can alternatively be
three-dimensional or have any other suitable number of dimensions.
In one variation, a virtual model of the waste container contents
can be created based on one or more measurements. The virtual model
can be 2-D, 3-D, or have any suitable number of dimensions. The
virtual model can be time-based, such that the model can function
as a record of the waste buildup in the container over time.
Recording the image preferably includes operating the respective
sensor in a capture mode. Recording the image can additionally
include emitting a light having a predetermined set of wavelengths
concurrently, within a predetermined period of time before or
after, or at any suitable time relative to operating the sensor in
the capture mode. The light can be directed in the same direction
as the sensor active area, in a direction opposing the sensor, in a
direction perpendicular or at any other suitable angle relative to
the sensor direction. One or more light sources can be concurrently
or sequentially used for the same image or sequential images.
[0042] In a first example, the image can be a full-color image 32,
wherein the image can subsequently be used to determine the shape
of the constituent waste objects, the source of the material (e.g.,
the brand of the material), or any other suitable parameter.
[0043] In a second example, the image can be a reflected light
intensity measurement, wherein the image is subsequently used to
determine the light reflectivity of the waste content.
[0044] In a third example, the image can be a multispectral image,
wherein the multispectral image can be subsequently be used to
determine the water content, organic content, heat emission, or any
other suitable content parameter. In a specific example, the
multispectral image can be recorded in the 600-690 nm range and
used to determine whether there are man-made objects, such as
polymers, in the content of a compost container. In a second
specific example, the multispectral image can be recorded in the
thermal infrared range (e.g., 10400-12500 nm) and used to determine
the amount of heat emitted by the waste, which can be indicative of
the number of microbes in the content, the degradation state of the
content, the amount of volatile organics produced, or used to
determine any other suitable content parameter.
[0045] In a fourth example, the image can be a hyperspectral image
that is used to determine the volume, concentration, and/or
location of a chemical gas. However, any other suitable image can
be recorded and used in any other suitable manner.
[0046] In a second variation, the content measurement is a content
identifier. The content identifier can be attached to the content
by a manufacturer, but can alternatively be attached by an
intermediate user or by any other suitable entity. The content
identifier is preferably a short-range communication identifier,
but can alternatively be a long-range communication identifier.
Examples of the content identifier include an RFID identifier, NFC
identifier, barcode, or any other suitable identifier. In this
variation, the content sensor 200 can be a communication receiver,
such as an RFID scanner, NFC scanner, or barcode scanner. However,
any other suitable content identifier and content sensor can be
used.
[0047] In a third variation, the content measurement is a material
property measurement (material parameter). Examples of material
property measurements (material parameters) include acoustical
properties (e.g., acoustic absorption, container resonance, etc.),
chemical properties (e.g., corrosion, corrosion resistance, pH,
reactivity, surface energy, surface tension, hygroscopy, etc.),
electrical properties (e.g., resistivity, conductivity, dielectric
constant or strength, permittivity, permeability, electromagnetic
field strength, etc.), environmental properties (e.g., temperature,
pressure, light, humidity, etc.), magnetic properties (e.g.,
diamagnetism, hysteresis, permeability, etc.), mechanical
properties (e.g., compressive strength, hardness, plasticity,
resilience, roughness, weight, density, volume, etc.), optical
properties (e.g., absorptivity, color, luminosity,
photosensitivity, reflectivity, refractive index, scattering,
transmittance, etc.), temperature, moisture, or any other suitable
property. In this variation, the content sensor 200 can be a
material property sensor, such as a microphone, ion meter, chemical
compound sensor (e.g., methane sensor), resistometer, current
sensor, voltage sensor, magnet, coil, force application mechanism,
weight sensor (e.g., scale), optical sensor, or any other suitable
sensor. Examples of environmental sensors can include ambient light
sensors, humidity sensors, pressure sensors, temperature sensor, or
any other suitable sensor capable of measuring an environmental
parameter. However, any other suitable measurement can be recorded
by any other suitable sensor.
[0048] Recording the content measurement S100 can additionally
include recording a baseline signal, which functions to provide a
measurement of a signal provided by an external signal source. The
baseline signal is preferably measured by a secondary sensor,
different from the content sensor 200, but can alternatively be
measured by the secondary sensor (e.g., wherein the content sensor
200 measures the baseline signal and content measurement
sequentially or in any other suitable order) or by any other
suitable sensor. The baseline signal that is measured is preferably
the same signal type (e.g., wavelength, etc.) as that measured by
the content sensor 200, but can alternatively be different, wherein
the different signal is preferably related to or influences the
content measurement. The baseline signal can be measured
concurrently with the content measurement, measured within a time
period of the content measurement (e.g., before or after), or
measured at any other suitable time.
[0049] In a first variation in which the signal measured by the
content sensor 200 is provided by an external source, the baseline
signal can be used to normalize or otherwise correct the content
measurement. For example, the intensity of ambient light can be
measured as the baseline signal and used to adjust the color
intensities extracted from a full spectrum image (e.g., captured
using a CCD) configured to record sunlight reflected by
objects.
[0050] In a second variation in which the signal measured by the
content sensor 200 is provided by a system emitter 220, the
baseline signal can be used to correct the content measurement for
noise imposed by the external environment. For example, the ambient
noise levels and/or patterns can be measured and used to remove
and/or correct the sound of waste falling into the container.
[0051] In a third variation, the baseline signal can be used to
determine the difference between a parameter of the signal provided
by an external source and a desired parameter. For example, the
method can include measuring the ambient light intensity,
determining the amount of auxiliary light that is required to
obtain a target light intensity (e.g., wherein the auxiliary light
is emitted in response to the ambient light intensity falling below
an intensity threshold), controlling a light source to provide
auxiliary light (e.g., a flash), and recording an image
concurrently or within a threshold time period of auxiliary light
emission. However, the baseline signal measurement can be used in
any other suitable manner.
[0052] Extracting a set of content parameters from the measurement
S200 functions to analyze the measurement to determine indicators
of the waste composition or material. The content parameters are
preferably extracted each time a set of measurements are recorded,
but can alternatively be extracted at a predetermined frequency,
after a predetermined number of measurement sets are recorded, or
extracted at any other suitable frequency. The content parameters
are preferably extracted by a computing system remote from the
monitoring system 100, but can alternatively be extracted by the
monitoring system 100 or any other suitable computing system. The
content parameters can be extracted for a single piece of waste,
for a portion of the total waste associated with (e.g., contained
within) the container at the time of content measurement, for the
entirety of the waste associated with (e.g., contained within) the
container, or for any other suitable set of waste objects
associated with the container. One or more content parameters
(e.g., a set or plurality) of content parameters can be extracted
from the measurement.
[0053] The content parameters extracted from the measurement can
include material parameters (e.g., as disclosed above), object
boundaries (e.g., of individual objects, the main body of waste
within the container, etc.), brand identifiers (e.g., brand names,
trademarks, barcodes, etc.), content status (e.g. structural
status, such as crumpled or uncrumpled, decomposition status,
etc.), or any other suitable parameter indicative of a
characteristic of the content. Alternatively, when the measurement
is a product or object identifier, the content parameter can be
determined based on the identifier. Alternatively, the content
parameter can be a change of a material parameter, object parameter
(e.g., container fill rate, container fill acceleration), or any
other suitable change over time. However, the content parameter can
be any other suitable measure indicative of content
classification.
[0054] The content parameters can be determined for the entirety of
the measurement, but can alternatively be determined on a
pixel-by-pixel basis (e.g., wherein a parameter value is determined
for each pixel then summed, averaged, or otherwise processed for a
set of pixels), determined from a portion of the measurement (e.g.,
one or more pixels), determined based on multiple measurements, or
be determined based on any other suitable set or subset of
measurements. For example, the reflectivity of content (e.g.,
indicative of content material composition) can be determined based
on a ratio of white to black over an entire grayscale image, can be
determined by determining the ratio for each pixel or set of pixels
then summed over the entire image, or determined in any other
suitable manner.
[0055] The content parameters can be determined from a single
content measurement, from a content measurement and a baseline
measurement, from a first and a second content measurement taken
within a predetermined period of time, from a first and a second
content measurement taken at least a predetermined period of time
apart (e.g., wherein the first and second content measurements are
preferably the same type of measurement but can alternatively be
different measurements), or from any other suitable set of
measurements.
[0056] In an example of determining the content parameters from a
single content measurement, a full color image can be analyzed to
extract object boundaries. In an example of determining the content
parameters from a content measurement and a baseline measurement,
the intensities of one or more wavelengths of interest are
extracted from a full color image and corrected by the ambient
light intensity measurement.
[0057] In an example of determining the content parameters from a
first and a second content measurement taken within a predetermined
period of time, a full color image is used to identify object
boundaries and/or generate a virtual representation of the objects
within the waste container, wherein the object boundaries and/or
virtual representation are used to identify parameter values
corresponding to the object in a second content measurement taken
within a predetermined period of first content measurement
recordation, such as a multispectral image. In a specific example,
the absolute or relative location of a pixel of the object in the
full color image is determined and used to identify the
corresponding set of pixels in the second content measurement. In a
second example, a full color image is used to identify the change
in volume of the contents within the container, an audio recording
is used to identify the mass of the newly added waste, and the
volume and mass can be used to determine the density of the newly
added waste, which can subsequently be used to determine the
composition of the waste.
[0058] In an example of determining the content parameters from a
first and second content measurement taken at least a predetermined
period of time apart, the first and second content measurements can
be full color images, wherein the volume of the content within the
container can be determined from each measurement and compared to
obtain a change in waste volume over time.
[0059] Extracting the content parameter from the measurement S200
preferably includes determining the content parameter based on the
signal values, but can alternatively include otherwise extracting
the content parameter from the measurement. Extracting a content
parameter can include extracting the content parameter from an
image or set of images S220, extracting the content parameter from
an audio clip, identifying an identifier based on the measured
signal (e.g., processing an RF signal to extract an identifier), or
extracting the content parameter in any other suitable manner.
[0060] Extracting a content parameter from an image S220 preferably
includes applying image processing techniques to the image to
extract gradients in intensity, saturation, color, or any other
suitable light parameter, identify edges or borders, identify
objects, or to extract any other suitable set of content parameters
from the image. Examples of image processing techniques include
computer vision methods, appearance methods, feature methods,
optical character recognition methods (e.g., to identify trademarks
or brand names), or any other suitable methods.
[0061] In variations wherein the image is captured after waste has
been deposited into the waste container 20 (e.g., when the waste is
static or has stopped falling), the content parameters extracted
from the one or more images can be extrapolated to determine the
content parameters for the entire contained waste mass (e.g.,
assumed to be representative of the entire waste mass, etc.).
Alternatively, one or more types of images can be combined to
determine the content parameters for the body of waste as a whole.
For example, the mass of conductive material (e.g., metal) can be
determined based on the conductivity of the entire body of waste.
In variations wherein the image is captured as the waste falls into
the waste container, the content parameters can be determined for
the newly added waste, the body of waste as a whole, for each
object, or for any suitable subset of the waste.
[0062] Examples of computer vision methods include shape or pattern
recognition based on supervised or unsupervised machine learning
techniques, segmentation techniques, point of interest
identification, or any other suitable computer vision method. For
example, a machine can be trained to recognize empty chip bags
based on a set of empty chip bag images, wherein the machine can
subsequently be used to identify empty chip bags in the image.
[0063] Examples of appearance methods include edge matching (e.g.,
using Canny edge detection, template comparison, etc.), divide and
conquer searching, grayscale matching, gradient analysis (e.g.,
matching), histograms of receptive field responses, shape
recognition based on supervised or unsupervised machine learning
techniques, eigenvector matching, or any other suitable appearance
method.
[0064] In one example of edge matching, edges (e.g., viewpoint
dependent or independent edges) are identified within the image
(e.g., using search-based methods, zero-crossing based methods, or
any other suitable edge detection method) and compared with an
object template to identify objects. The template edges can be
rotated, partially obscured, scaled, or otherwise adjusted to match
the edges in the image. The template can additionally be aligned
with the image, combined with other templates, or otherwise used.
Edge sets having beyond a threshold similarity with the template
are preferably assigned as the object associated with the template.
Alternatively, the number of overlapping edges between the template
and image can be counted to identify the object, the number of
template edge pixels within a predetermined pixel distance from an
image edge can be counted to identify the object, the probability
distribution of the distances between the edges in the image and
the edges in the template can be used to estimate the likelihood
that a set of templates correctly anticipate the objects in the
image. However, any other suitable edge matching technique can be
used.
[0065] In one example of divide-and-conquer searching, the method
includes determining a score for an image portion based on the
portion similarity with a portion of a object template, the portion
resolution, portion gradient uniformity, or based on any other
suitable parameter, and recursively segmenting the portion of the
image into sub-portions in response to the score falling below a
threshold. However, any other suitable divide-and-conquer search
method can be used.
[0066] In one example of grayscale matching, the method includes
computing the pixel distance as a function of both pixel position
and pixel intensity from an image. The grayscale match can be
determined from a single image or can be determined based on
multiple images, each associated with a different illumination
intensity, can be compared to extract the edges. This method can be
applied to images recorded using any suitable set of
wavelengths.
[0067] Examples of feature methods include searching through
interpretation trees, iterative testing, pose consistency, pose
clustering, invariance, geometric hashing, scaleoinvariant feature
transform, speeded up robust features, but any other suitable
feature identification method can be used. In one example of
searching through an interpretation tree, a tree of possible waste
objects is used. For each set of boundaries identified in the
image, the tree is searched for a probabilistic match. Historically
identified objects associated with the container can have higher
probabilities than objects that were not historically identified.
However, search trees can be otherwise used.
[0068] Images can suffer from insufficient content information,
particularly in variations wherein the image is captured after
waste has been deposited into the waste container (e.g., when the
waste is static or has stopped falling). This is because the image
typically only captures information in a fixed set of planes or
views, and cannot record measurements of waste that is obscured by
secondary waste proximal the sensor or emitter 220. To resolve this
issue, the content parameters extracted from the one or more images
can be extrapolated to determine the content parameters for the
entire contained waste mass (e.g., assumed to be representative of
the entire waste mass, etc.). Alternatively, one or more types of
images or measurements can be combined to determine the content
parameters for the entire waste mass. For example, an
electromagnetic measurement can be combined with a volume
measurement to estimate the ferrous material content in the waste
mass. However, the content parameters of obscured waste can be
otherwise determined.
[0069] Extracting the content parameters from the measurement S200
can include extracting an audio pattern from the audio measurement
and/or parameters of the audio pattern. For example, the audio
frequency can be extracted and subsequently used to determine the
type of material that the waste is made of (e.g., wherein metallic
objects are associated with different frequencies than glass
objects). In a second example, a wavelength can be extracted and
subsequently used to determine the type of material that the waste
is made of or the shape of the object (e.g., wherein different
wavelengths are associated with different material compositions or
shapes).
[0070] Extracting the content parameters from the measurement S200
can include determining a composition of the waste content based on
an electromagnetic measurement. For example, the permeability of an
electromagnetic field through the body of the waste can be
indicative of the ferrous material content of the waste.
[0071] Characterizing the content within the waste container based
on the set of content parameters S300 functions to determine a set
of content metric values for the waste within the container,
wherein the metric values 14 can be used to select the waste
containers to be emptied. The content is preferably characterized
each time a set of measurements are recorded, but can alternatively
be characterized at a predetermined frequency, after a
predetermined number of measurement sets are recorded, or
characterized at any other suitable frequency. The secondary system
preferably characterizes the content, but the monitoring system 100
can alternatively characterize the content. Characterizing the
content can include categorizing the content by material, object,
parameter, or based on any other suitable category, wherein the
material, object, and parameter are the metrics. Alternatively,
characterizing the content can include calculating one or more
indices for the content, wherein the indices are the metrics.
However, any other suitable value for any other suitable content
metric can be determined. Examples of indices that can be
calculated include purity indices, plant indices (e.g., organic
material indices, such as NDVI), contamination index, value index,
or any other suitable index. The purity index is preferably
calculated for a given material (e.g., metal, plastic, paper,
organic material, etc.), or subset thereof, object (e.g., bottle,
bag, box, etc.), waste type (e.g., recyclable, compost, landfill,
etc.), brand, or for any other suitable category, but can
alternatively be a measure of material mixing, material uniformity
(e.g., material distribution) throughout the container volume, or
be a measure of any other suitable parameter. The purity index is
preferably by volume (e.g., a volume ratio), but can alternatively
be by mass or by any other suitable parameter. Examples of material
subsets that can be identified include cardboard, plastics (e.g.,
PET, PTFE, etc.), metals, organics, paper products (e.g., printer
paper, newspaper, etc.), ceramics, construction material, e-waste
(e.g., copper, silicon, etc.), aluminum, copper, steel,
biohazardous material, textiles, chemicals, animals, fecal matter,
food scraps, packaging, Styrofoam, or any other suitable
material.
[0072] The purity index can be a mass ratio, volume ratio, degree
measure, or any other suitable ratio. Each container can be
associated with one or more indices.
[0073] In one example, the purity index can be the percentage of a
compostables in the waste container, wherein the mass of the
compostables can be determined based on volumetric measurements
(e.g., from images) and the known or estimated density of the
compostable material, and the mass of the total waste in the
container can be determined from volumetric measurements (e.g.,
from the same or different images as those used to identify the
compostable volume) and a weight measurement.
[0074] In a second example, the method can include identifying
brand trademarks (e.g., brand names, colors, etc.) in the waste
(e.g., using OCR or other image recognition methods), retrieving
packaging material information such as packaging material
composition (e.g., glass, type of plastic, etc.), form factor, or
any other suitable information based on the brand trademarks (e.g.,
from an on-board or remote storage system), and calculating the
mass of a given type of packaging material based on the number of
times a trademark is detected and the retrieved information.
[0075] In a third example, the method can include recording thermal
measurements of a plurality of points within the waste container
(e.g., using multiple thermal sensors or taking a thermal image 34
of the waste container interior), determining the distribution of
heat or heat sources within the waste container (e.g., indicative
of organic waste decomposition), and determining a degree of
material mixing based on the heat distribution. For example, an
index value associated with a high degree of material mixing can be
determined in response to substantially even heat distribution
throughout the container or heat gradients below a threshold
gradient value, and a second index value associated with a low
degree of material mixing can be determined in response to
segregation between high heat zones and low heat zones or heat
gradients above a threshold gradient value that is the same as or
different from the first gradient value.
[0076] In a fourth example, the method can include identifying
contaminants within the waste container (e.g., using object
recognition) and calculating a contamination index based on the
mass, volume, orientation, or other parameter of the contaminants.
For example, recycling contaminants such as plastic bags, shredded
paper, scrap metal, hazardous waste, diapers or other bio-hazardous
waste, non-recyclable plastics (e.g., Styrofoam), flattened
containers, capped jars, liquids, ceramics, and frozen food
containers can be identified within the waste container, the mass
and distribution of contaminants determined, and the contamination
index calculated based on the mass and distribution of the
contaminants. However, the contamination index can be otherwise
determined.
[0077] Characterizing the content S300 can additionally include
determining a monetary value for the content within the container
(content value). The monetary value is preferably determined based
on market rates for the waste and the content characterization. The
market rate can be a rate for the waste material retrieved from a
global market, received from a receiving facility 40 (e.g.,
landfill, recycling plant, etc.), bidder on an exchange, or
obtained from any other suitable source. The market rate is
preferably updated in near real time, but can alternatively be
updated in response to a request or at any other suitable
frequency. In one variation, the content value is determined based
on the market value of a given type of material and the mass of the
given type of material within the container or other content
parameter for the container. For example, the content value of a
container with 10 lbs of cardboard is preferably more than the
content value of a container with 5 lbs of cardboard.
[0078] In another variation, the content value is determined based
on the market value of a given type of material, the mass of the
given type of material within the container (or other content
parameter for the container), and the purity index or contamination
index for the material, wherein higher contamination indices or
lower purity indices can lower the content value. For example, the
content value of a waste container containing 50% glass preferably
has a higher content value than a waste container containing 25%
glass and a mixture of other materials. In another example, the
content value of a waste container containing 50% glass that is
segregated from the remainder of the material (e.g., by bags,
located in a different compartment or area of the container, etc.)
preferably has a higher content value than a waste container
containing 50% glass interspersed with the remainder of the
material.
[0079] In another variation, the content value is determined based
on the purity index or contamination index. The content value is
preferably a linear function of the purity index, but can
alternatively be a logarithmic function, exponential function, step
function, or any other suitable function of the purity index or
contamination index. The content value preferably varies directly
with the purity index and indirectly with the contamination index.
The content value is preferably determined by the receiving
facility 40, but can alternatively be calculated or otherwise
determined.
[0080] Characterizing the content S300 can additionally include
predicting waste changes. Predicting waste changes can include
determining future changes in the parameters or indices for the
entirety of the waste within the container, such as anticipated
volume changes, material distribution changes (e.g., composition
changes), spatial distribution changes, or any other suitable bulk
change. These changes can result from predicting the parameters of
the waste that will be deposited into the waste container in the
future. Predicting waste changes can also include anticipating
future changes in the waste currently retained by the waste
container, such as chemical and/or physical changes to the waste
due to decomposition. The waste changes are preferably determined
based on historical waste data for the waste container, but can
alternatively be determined based on historical waste data for a
population of similar waste containers (e.g., waste containers
associated with a certain type of waste, such as recycling bins, or
waste containers associated with a similar entity or business type,
etc.), be determined based on a database, or be determined in any
other suitable manner.
[0081] Routing a waste collection vehicle based on the content
metric values S400 functions to more efficiently allocate waste
management resources. Routing the waste collection vehicles based
on the content characterization can function to maximize monetary
returns to the waste collectors, minimize costs to the waste
collectors, increase the efficiency of the receiving facilities, or
otherwise influence waste collection, waste processing, or any
other suitable waste management process.
[0082] The waste collection vehicles are preferably routed in
response to the occurrence of a routing event. The routing event
can be the passing of a predetermined period of time (e.g., wherein
the waste collection vehicles are routed at a predetermined
frequency), in response to receipt of a user request, in response
to a threshold number of waste containers satisfying a condition
(e.g., a volume condition, value condition, purity condition,
etc.), in response to determination of an adverse change (e.g.,
anticipated contaminant deposition into an otherwise pure waste
container), or in response to the occurrence of any other suitable
event. The waste collection vehicle preferably travels along the
selected route, collects waste from select waste containers along
the route, transports the waste to an endpoint, and deposits the
waste at the endpoint. The waste collection vehicle can
additionally verify the content parameters and/or content
characterizations (e.g., purity, contamination, value, etc.) with a
monitoring system 100 on the vehicle (e.g., on the hopper, on the
arm, or arranged in any other location on the vehicle).
[0083] Routing the waste collection vehicle based on the content
metric values 400 preferably includes selecting a subset of waste
containers for collection (retrieval) by a waste collection
vehicle. The subset of waste containers is preferably selected to
meet a threshold parameter or index value. The method preferably
additionally includes recording measurements, determining content
parameters, and characterizing the content for a plurality of waste
containers. The waste from the subset of waste containers are
preferably collected by the same waste collection vehicle, but can
alternatively be collected by different collection vehicles.
Multiple subsets of waste containers can be selected for the same
or different collection vehicles. The waste containers are
preferably included in a single subset, but can alternatively be
included in multiple subsets.
[0084] In a first variation, the subset of waste containers are
selected based on the respective volumes of the waste container.
The waste containers that have content volumes exceeding a volume
threshold are selected for inclusion in the subset. The volume
threshold is preferably predetermined, but can alternatively be
dynamically determined (e.g., based on receiving facility charges,
value of the content, etc.) or otherwise determined.
[0085] In a second variation, the subset of waste containers are
selected based on the purity index and/or contaminant index. The
waste containers of the subset are preferably selected to meet a
target total purity index (e.g., for the waste contained in the
waste collection vehicle at the end of the route), but containers
associated with purity indices falling within a predetermined
range, exceeding a purity index threshold, or satisfying any other
suitable condition can additionally or alternatively be included in
the subset. The purity index threshold is preferably predetermined,
but can alternatively be dynamically determined (e.g., based on
receiving facility charges) or otherwise determined. In a first
example, a first waste container having a 50% purity index for
recyclables and a second waste container having a 70% purity index
for recyclables can both be selected for inclusion in the subset
when the target total purity index is 60%. In a second example,
waste containers having purity indices for corrugated cardboard
over a threshold purity index value are selected for inclusion in
the subset. In a third example, waste containers having a purity
index below a threshold purity index value or having a
contamination index above a threshold contamination index value are
selected for inclusion in the subset. The waste containers included
in the subset can additionally satisfy the volume condition, as
discussed in the first variation.
[0086] In a third variation, the subset of waste containers is
selected based on the content value. The waste containers of the
subset are preferably selected to meet or maximize a total content
value (e.g., for the waste contained in the waste collection
vehicle at the end of the route), but can alternatively be selected
to meet an average content value for the totality of content
collected during the route, selected because the respective content
value falls within a value range or exceeds a cost threshold, or
selected because the content satisfies any other suitable
condition. The waste containers included in the subset can
additionally satisfy the volume condition and/or purity index
condition, as discussed in the first and second variations. The
respective content values, volumes, purity indices, contamination
indices, or any other suitable waste characterization or parameter
can be entered into an optimization equation to determine the
subset of waste containers marked for pickup. In one example, only
waste containers having purity indices for recyclables above a
threshold index value and having content values above a threshold
value are selected. In a second example, a first waste container
having a high content value and a second waste container having a
low content value and purity index can be included in the subset in
response to the second waste container exceeding a volume threshold
(e.g., requiring urgent collection). In a third example, a first
waste container having a high content value for copper and a low
volume can be marked for collection while a second waste container
having a low content value for copper and a high volume close to or
exceeding the volume threshold is not marked for collection when
the value of the first waste container exceeds the cost of not
collecting the second container. However, the waste containers can
be otherwise selected.
[0087] In a fourth variation, the subset of waste containers is
selected based on the parameters of the predicted waste changes
(e.g., magnitude of waste change, rate of waste change,
acceleration of waste change, etc.). The subset can additionally be
selected based on the instantaneous waste parameters or indices.
For example, a first waste container is selected for inclusion in a
waste container subset to be emptied at a first time range, even
though the first waste container had not met the volume threshold,
when the purity index for the waste container is anticipated to
decrease after the first time range.
[0088] However, the subset of waste containers can be selected
based on any other suitable combination of content parameters and
characterizations.
[0089] Routing the waste collection vehicle based on the content
characterization S400 can additionally include selecting a route
between the subset of waste containers for the waste collection
vehicle. The route can be selected to optimize fuel use, vehicle
operation cost, user satisfaction, pickup ease (e.g., based on
predicted or instantaneous weather, etc.), or any other suitable
parameter.
[0090] Routing the waste collection vehicle S400 can additionally
include selecting an endpoint for the waste collection vehicle. The
endpoint is preferably a receiving facility, such as a recycling
facility, composting facility, landfill, or any other suitable
facility. The endpoint is preferably selected based on the waste
characterization (e.g., indices, value, etc.) of the waste to be
collected and/or collected waste, but can alternatively or
additionally be selected based on the content parameters or based
on any other suitable factor. For example, a recycling facility can
be selected for waste collection vehicles collecting waste from
waste containers having a purity index for recyclables over an
index value threshold, a composting facility can be selected for
waste collection vehicles collecting waste from waste containers
having a purity index for compost over an index value threshold,
and landfill can be selected for waste collection vehicles
collecting waste from waste containers having a contamination index
over an index value threshold or purity indices under an index
value threshold. In another example, a first facility (e.g.,
recycling or composting facility) can be selected in response to
the content value exceeding a threshold value (e.g., the cost to
collect waste from the selected waste containers, $0, or another
monetary value), and a second facility (e.g., a landfill) can be
selected in response to the content value falling below a threshold
value (e.g., below $0).
[0091] The endpoint can be predetermined or dynamically determined.
For example, in response to detection of an unexpected contaminant
entering the waste collection vehicle hopper based on a measurement
from a monitoring system 100 attached to the waste container or the
hopper, the purity index, cost, or other parameter can be
dynamically recalculated, and the waste collection vehicle
dynamically rerouted based on the new parameter value. In a
specific example, if the contaminant caused the total waste value
to be unacceptable to the previously selected endpoint (e.g.,
recycling facility), a second endpoint, such as a landfill, can be
selected for the waste collection vehicle. The subset of waste
containers can additionally be dynamically adjusted, such that the
subset assigned to the waste collection vehicle can include waste
containers having contamination indices above a threshold value
(e.g., waste containers containing waste that would have had to go
to the landfill).
[0092] A single endpoint is preferably determined for each waste
collection vehicle route (e.g., duration between the vehicle
collection vehicle leaving a start point, collecting waste from at
least one container, and ending at an endpoint), but multiple
endpoints can alternatively be selected for each route. In one
example, the waste containers can include layers of material,
wherein each material layer has a different purity index for a
different material (e.g., the first layer is glass-rich, the second
layer is cardboard-rich, and a third layer is plastic-rich). In
this variation, the waste collection vehicle can separate the
layers during collection, such as by dumping the contents of the
container into a glass hopper until the second layer is
substantially reached, and multiple endpoints corresponding to the
different material types (e.g., glass, cardboard, and plastic
processing facilities, respectively) can be selected as the
endpoints for the route.
[0093] An alternative embodiment preferably implements the above
methods in a computer-readable medium storing computer-readable
instructions. The instructions are preferably executed by
computer-executable components preferably integrated with a vehicle
routing system that functions to select waste containers for waste
collection during a route based on analysis of the waste in the
waste containers, and to select an endpoint for the route. The
vehicle routing system can include a waste measurement system that
functions to measure the parameters of waste within a set of waste
containers one or more times between waste collection, and a waste
analysis system that functions to analyze the waste measurement to
determine the waste composition, value, or any other suitable
parameter. The computer-readable medium may be stored on any
suitable computer readable media such as RAMs, ROMs, flash memory,
EEPROMs, optical devices (CD or DVD), hard drives, floppy drives,
or any suitable device. The computer-executable component is
preferably a processor but the instructions may alternatively or
additionally be executed by any suitable dedicated hardware
device.
[0094] Although omitted for conciseness, the preferred embodiments
include every combination and permutation of the various system
components and the various method processes.
[0095] As a person skilled in the art will recognize from the
previous detailed description and from the figures and claims,
modifications and changes can be made to the preferred embodiments
of the invention without departing from the scope of this invention
defined in the following claims.
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