U.S. patent application number 14/745920 was filed with the patent office on 2017-09-21 for system and method for reporting a status of an asset.
The applicant listed for this patent is SkyBitz, Inc.. Invention is credited to Rich Battista.
Application Number | 20170268883 14/745920 |
Document ID | / |
Family ID | 57587904 |
Filed Date | 2017-09-21 |
United States Patent
Application |
20170268883 |
Kind Code |
A9 |
Battista; Rich |
September 21, 2017 |
System and Method for Reporting a Status of an Asset
Abstract
A system and method for reporting a status of an asset is
described. In one embodiment, an asset status is determined based
on configurable parameters to thereby enable accurate reporting of
departures and arrivals of an asset.
Inventors: |
Battista; Rich; (Ashburn,
VA) |
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Applicant: |
Name |
City |
State |
Country |
Type |
SkyBitz, Inc. |
Herndon |
VA |
US |
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Prior
Publication: |
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Document Identifier |
Publication Date |
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US 20160370184 A1 |
December 22, 2016 |
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Family ID: |
57587904 |
Appl. No.: |
14/745920 |
Filed: |
June 22, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12886098 |
Sep 20, 2010 |
9064421 |
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14745920 |
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12361089 |
Jan 28, 2009 |
7804394 |
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12886098 |
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11377651 |
Mar 17, 2006 |
7498925 |
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12361089 |
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60715592 |
Sep 12, 2005 |
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60750791 |
Dec 16, 2005 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/063 20130101;
G01C 21/20 20130101 |
International
Class: |
G01C 21/20 20060101
G01C021/20; G06Q 10/06 20060101 G06Q010/06 |
Claims
1. A method, comprising: retrieving a configurable time period
parameter from storage in a mobile terminal device attached to an
asset; retrieving a configurable percentage parameter from storage
in the mobile terminal device; during a time period spanning a
length of time determined by the configurable time period
parameter, determining a first non-zero portion of time that the
asset operated in a first operational condition and a second
non-zero portion of time that the asset operated in a second
operational condition; and initiating a transmission of a status
report to a site remote from the asset when it is determined that
the percentage of the first non-zero portion of time relative to
the time period is less than a configurable percentage of the time
period determined using the retrieved configurable percentage
parameter.
2. The method of claim 1, wherein the first operational condition
is a motion condition and the second operational condition is a
no-motion condition.
3. The method of claim 1, wherein the first operational condition
is a no-motion condition and the second operational condition is a
motion condition.
4. The method of claim 1, wherein the status report includes time
and position information.
5. The method of claim 1, further comprising receiving, by the
mobile terminal device, the configurable time period parameter and
configurable percentage parameter via satellite.
6. A device, comprising: a sensor that is configured to measure a
state of an asset; a memory that is configured to store a
configurable time period parameter and a configurable percentage
parameter; and a processor that is configured to determine, during
a time period spanning a length of time determined by the
configurable time period parameter, a first non-zero portion of
time that the asset operated in a first operational condition and a
second non-zero portion of time that the asset operated in a second
operational condition, and to initiate a transmission of a status
report to a site remote from the asset when it is determined that
the percentage of the first non-zero portion of time relative to
the time period is less than a configurable percentage of the time
period determined using the retrieved configurable percentage
parameter.
7. The device of claim 6, wherein the first operational condition
is a motion condition and the second operational condition is a
no-motion condition.
8. The device of claim 6, wherein the first operational condition
is a no-motion condition and the second operational condition is a
motion condition.
9. The device of claim 6, wherein the status report includes time
and position information.
10. The device of claim 6, further comprising a receiver that is
configured to receive the configurable time period parameter and
configurable percentage parameter via satellite.
11. A method, comprising: retrieving a configurable time period
parameter from storage in a mobile terminal device attached to an
asset; retrieving a configurable percentage parameter from storage
in the mobile terminal device; during a time period spanning a
length of time determined by the configurable time period
parameter, determining a first non-zero portion of time that the
asset operated in a first operational condition and a second
non-zero portion of time that the asset operated in a second
operational condition; and initiating a transmission of a status
report to a site remote from the asset when it is determined that
the percentage of the first non-zero portion of time relative to
the time period is greater than a configurable percentage of the
time period determined using the retrieved configurable percentage
parameter.
12. The method of claim 11, wherein the first operational condition
is a motion condition and the second operational condition is a
no-motion condition.
13. The method of claim 11, wherein the first operational condition
is a no-motion condition and the second operational condition is a
motion condition.
14. The method of claim 11, wherein the status report includes time
and position information.
15. The method of claim 11, further comprising receiving, by the
mobile terminal device, the configurable time period parameter and
configurable percentage parameter via satellite.
Description
[0001] This application is a continuation of non-provisional patent
application Ser. No. 12/886,098, filed on Sep. 20, 2010, which is a
continuation of non-provisional patent application Ser. No.
12/361,089 (Now U.S. Pat. No. 7,804,394), filed on Jan. 28, 2009,
which is a continuation of non-provisional patent application Ser.
No. 11/377,651 (now U.S. Pat. No. 7,498,925), filed Mar. 17, 2006.
Non-provisional application Ser. No. 11/377,651 claims the benefit
of and priority to provisional application No. 60/715,592, filed
Sep. 12, 2005, and provisional application No. 60/750,791, filed
Dec. 16, 2005. Each above-identified application is incorporated
herein by reference in its entirety.
BACKGROUND
[0002] Field of the Invention
[0003] The present invention relates generally to monitoring and
tracking and, more particularly, to a system and method for
reporting a status of an asset.
[0004] Introduction
[0005] Tracking mobile assets represents a growing enterprise as
companies seek increased visibility into the status of a service
fleet (e.g., long-haul delivery fleet). Visibility into the status
of a service fleet can be gained through mobile terminals that are
affixed to service vehicles. These mobile terminals can be designed
to generate position information that can be used to update status
reports that are provided to customer representatives.
[0006] In generating status reports to a centralized facility, the
mobile terminal can generate position information through the
reception of satellite position signals such as that generated by
the GPS satellite network. Processing these GPS signals, generating
position information, and transmitting status reports to the
centralized facility comes at the expense of the power requirements
at the mobile terminal. Here, an increased number of reporting
cycles reduces the effective battery life of the mobile terminal,
thereby increasing the maintenance and field costs of the mobile
terminals. Thus, what is needed is a system and method for
increasing visibility into the mobile assets, while maintaining a
reasonable battery life of the mobile terminal.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] In order to describe the manner in which the above-recited
and other advantages and features of the invention can be obtained,
a more particular description of the invention briefly described
above will be rendered by reference to specific embodiments thereof
which are illustrated in the appended drawings. Understanding that
these drawings depict only typical embodiments of the invention and
are not therefore to be considered limiting of its scope, the
invention will be described and explained with additional
specificity and detail through the use of the accompanying drawings
in which:
[0008] FIG. 1 illustrates an embodiment of a satellite network in
communication with a mobile terminal.
[0009] FIGS. 2A and 2B illustrate an example of a timeline of
status reports generated by a moving asset.
[0010] FIG. 3 illustrates an embodiment of an adaptive motion
sensor system.
[0011] FIG. 4 illustrates an example of accelerometer data.
[0012] FIG. 5 illustrates results of filtering on raw accelerometer
data.
[0013] FIG. 6 illustrates an example of different motion
states.
[0014] FIG. 7 illustrates an example of integration to a motion
state.
[0015] FIG. 8 illustrates an example of histogram data.
[0016] FIG. 9 illustrates a block diagram of an embodiment of an
adaptive threshold process.
[0017] FIG. 10 illustrates an example of a match-filtered
histogram.
DETAILED DESCRIPTION
[0018] Various embodiments of the invention are discussed in detail
below. While specific implementations are discussed, it should be
understood that this is done for illustration purposes only. A
person skilled in the relevant art will recognize that other
components and configurations may be used without parting from the
spirit and scope of the invention.
[0019] In accordance with the present invention, a system and
method is provided that enables the acquisition and sending of
asset position information, start times, and stop times on an
on-demand or event driven basis. One example of an event is when a
mobile asset either starts or stops moving. It is a feature of the
present invention that this tracking mechanism provides the most
useful and valuable information about the movement of an asset to
the customer, and at the same time minimizes the amount of power
and bandwidth required, thereby reducing cost and extending battery
life of the mobile terminal.
[0020] To appreciate the advantages of the present invention, it
should be recognized that there is a difference between "data" and
"information". Data is used to send information. Data can therefore
be sent with or without any information in it. Energy or power is
required to collect data. Bandwidth and cost is required to send
data over a medium such as a satellite network. Ideally, data is
collected and sent only when it contains information.
[0021] For asset tracking, the information can include the change
of position and the time in which it occurred. If a position does
not change, there is no new information, and no need to collect and
send more data. One example of this is when a trailer is parked for
three weeks in a yard. Here, a regularly scheduled reporting rate
of once per day will have one report with information, and 20
reports with redundant data (or no information) since the position
or stop time hasn't changed. This example illustrates a tremendous
waste of power, bandwidth and cost. This waste can be eliminated by
detecting a stop event, then collecting and sending position and
stop-time information a single time. There is no need to collect
and send data again until the position changes or the asset starts
moving. When the asset does start moving, the position changes and
new information can then be sent. While moving, the position
continually changes, and the need for position reports can drive
the frequency of further updates. Many long-haul fleets are
interested in pickup and delivery only, and not location in route.
If position information is desired in route, the asset can either
be paged for position, or can be given a temporary scheduled
reporting rate (e.g., every 2 hours) over-the-air to leave a trail
to track the asset in route. When the asset stops, the temporary
scheduled reporting rate can be removed or lowered.
[0022] The quality of service from on-demand reporting is superior
to conventional once per day reporting. The problem with
once-per-day reports is that the information can be almost 24 hours
old when it is retrieved. Typically, customers want reports around
the same time of day or during "prime time." Prime time for
dispatch trailer tracking is in the morning between the hours of 4
AM to 10 AM. When dispatchers or other users arrive at work in the
morning, they want a recent position of where the trailers are,
typically within a few hours. Like other networks, including
cellular phone networks, everyone cannot use the network at the
same time. Either the users accept older positions, or the service
company expands the size of the network, which becomes very cost
ineffective. The solution to satisfy the user and the service
company is to use on-demand reporting.
[0023] With on-demand reporting, the user is satisfied because at
any time of day, morning or night, they can know where their
trailers are within minutes most of the time. This results because
trailers are stopped most of the time, much more than they are
moving. When a dispatcher looks at the position of an asset that
stopped two weeks ago, they immediately know where it is at the
moment they look. That's because it is stopped. Otherwise, if it
moved from that location, it would have sent an event indicating it
started to move. In the case where the asset is moving when an
inquiry is made, the position could be hours old or as long as the
unit keeps moving without stopping. If a two-hour reporting rate is
applied while moving, then the dispatcher knows where the asset is
within two hours, and on average, within 1 hour. This is far
superior then once per day position reporting.
[0024] To the service provider, on-demand service is easier to
provide than scheduled reporting during prime time. This is based
on the fact that most long-haul trucking companies operate at all
times of the day, where their assets start and stop at all
different times of day, and subsequently, position and start/stop
time information will be sent at all different times of day,
spreading the network usage out over the whole day and not just
during prime time. Even with companies that operate in the daytime,
the network usage will still be spread, and utilized more
efficiently than scheduled reporting.
[0025] In accordance with the present invention, the mobile
terminal of the present invention includes an adaptive motion
sensor that is used to detect movement of assets and initiate GPS
signal measurements for position determination. The adaptive motion
sensor also aids in the determination of arrival and departure
times.
[0026] In one embodiment, the adaptive motion sensor is an
independent processing unit within the mobile terminal and is
capable of implementing adaptive processing in software. This
adaptive processing automatically adjusts thresholds used to
determine whether an asset is moving or not moving. Normally these
thresholds are fixed and require manual adjustment for different
asset types since each asset type has different characteristics
(e.g., levels of vibration) while it is in motion. For example,
truck trailers ride rougher and vibrate at higher levels as
compared to cars, which ride smoother and vibrate at lower levels.
Cars would therefore require a lower threshold than the truck
trailer to detect the vibration.
[0027] In one vibration sensor embodiment, three valid states can
be defined: (1) no vibration where the engine is off and no
movement; (2) engine on but no movement; and (3) engine on and
movement. The adaptive processing can collect and process vibration
data to determine the levels of vibration for each state and
automatically adjust a threshold to determine whether the asset is
moving or not. Automatically or adaptively determining this
threshold alleviates a large amount of effort required to determine
this threshold manually. Not only will this reduce effort and cost
and make the use of motion sensors more scalable, but it will also
improve the reliability and performance of the motion detection
processing since it can find the optimum thresholds
automatically.
[0028] Prior to describing the details of a mobile terminal
incorporating an adaptive motion sensor system, a description of an
embodiment of an operational context in which the mobile terminal
can operate is first provided. FIG. 1 illustrates an embodiment of
a satellite network that includes operations gateway 102,
communicating with satellite gateway 104, and has one forward and
one return link (frequency) over satellite 106 to mobile terminal
120 located on the asset. The satellite waveform is implemented in
the Time Division Multiple Access (TDMA) structure, which consists
of 57600 time slots each day, per frequency or link, where each
slot is 1.5 seconds long. On the forward link, operations gateway
102 sends a message or packet to mobile terminal 120 on one of the
1.5 second slots to give instructions to global locating system
(GLS) component 124 via satellite modem processor 122. One example
is to instruct GLS component 124 to perform a GPS collection (e.g.,
code phase measurements) and transmit the data back to operations
gateway 102. When GLS component 124 of mobile terminal 120 receives
this forward command, it collects the GPS information and transmits
the data back on the return link, on the same slot, delayed by a
fixed time defined by the network. The delay is needed to decode
the forward packet, perform the GPS collect and processing, and
build and transmit the return packet.
[0029] From there, operations gateway 102 passes the information to
operation center 112, where the information is used to solve for
position and present the position information to the customer via
the internet. A detailed description of this process is provided in
U.S. Pat. No. 6,725,158, entitled "System and Method for Fast
Acquisition Position Reporting Using Communication Satellite Range
Measurement," which incorporated herein by reference in its
entirety.
[0030] It should be noted that the principles of the present
invention can also be applied to other satellite-based or
terrestrial-based location determination systems where the position
is determined at the mobile terminal independently, or at the
mobile terminal in combination with information received from
another location.
[0031] As illustrated in FIG. 1, mobile terminal 120 also includes
adaptive motion sensor 126. The main task of adaptive motion sensor
126 is to determine whether an asset is moving or not. From there,
together with the mobile terminal processor (not shown) and GLS
component 124 it can determine the arrival and departure times and
locations of an asset. When an asset begins to move, the adaptive
motion sensor 126 detects the motion or vibration and sends a
signal to the mobile terminal processor informing it that motion
has started. The mobile terminal processor then records the time
motion started, and signals to GLS component 124 to collect code
phase. The start time and the codephase are sent over the satellite
back to operations gateway 102 and operation center 112 where the
codephase is used to solve for position, and the start time is used
to generate the departure time. Conversely, when adaptive motion
sensor 126 determines motion has stopped it will again inform the
mobile terminal processor to collect time and codephase, and send
the information back to operations gateway 102. Operation center
112 solves for position, and the stop time is used to generate the
arrival time. The arrival and departure times along with their
locations can be supplied to the user via the Internet. As noted,
in an alternative embodiment, the mobile terminal could send a
position determined at the mobile terminal back to operations
center 112.
[0032] In one embodiment, adaptive motion sensor 126 has a layer of
filtering that is capable of filtering out unwanted starts and
stops and only transmits true arrival and departure information.
Adaptive motion sensor 126 can be configured to only transmit
starts or stops when the change in motion is maintained for a
configurable percentage of time. In this manner, only accurate
arrival and departure time information is transmitted using the
mobile terminal with the adaptive motion sensor. This layer of
filtering saves on unwanted transmissions, and hence power,
bandwidth, and cost.
[0033] In one embodiment, mobile terminal 120 is configured to
transmit a position report after the actual arrival or departure
times when the motion sensor has reached its "no-motion" or
"motion" times, respectively. The "motion" and "no-motion" times
can be separately configurable, for example, from one minute up to
two hours. This configurability can be used to allow more time to
exit an area of interest, or allow more time at rest stops along
the way.
[0034] In one embodiment, the user-configurable "motion
sensitivity" can be implemented as the percentage of time the asset
needs to remain in motion during the "motion time" to signal
motion. This is useful, for example, in maintaining a motion
condition while stopped at a traffic light or a rest stop.
Conversely, the user-configurable "no-motion sensitivity" can be
implemented as the percentage of time the asset needs to remain in
no-motion during the "no-motion" time to signal no-motion. This is
useful, for example, in maintaining a no-motion condition while
moving a trailer within a yard.
[0035] FIGS. 2A and 2B illustrate an example of a timeline of a
unit moving from point A to point E, and stopping in between. In
this example, two states are used for the adaptive motion sensor:
motion and no-motion. The user-configurable motion time is set at
15 minutes, while the user-configurable motion sensitivity is set
at 70%. The user-configurable no-motion time is set at 30 minutes,
while the user-configurable no-motion sensitivity is set at
70%.
[0036] The timeline begins at 10 AM when the asset begins to leave
a yard at point A on its trip to point E. When the adaptive motion
sensor determines a transition to the motion state, it records the
time of 10 AM. The asset then stops at a traffic light between
point A and point B for three minutes. During this time, the
adaptive motion sensor determines that the asset is in a no-motion
condition for those three minutes. It should be noted that even
with the existence of the motion condition prior to the traffic
light stop, the mobile terminal does not report that the asset has
departed point A. This results because the user-configurable motion
time has been set at 15 minutes. Thus, the motion time threshold
has not yet been reached. When the 15-minute motion time has
expired, the mobile terminal then determines whether the
user-configurable motion sensitivity has been satisfied. With a
motion sensitivity of 70%, the asset would need to maintain a
motion condition for at least 70% of the 15 minutes, or 10.5
minutes. In this example, the asset has maintained a motion
condition for 12 of the 15 minutes, therefore satisfying the motion
sensitivity threshold. With both the time and sensitivity
thresholds being met, the mobile terminal then transmits a message
to the operations center that the asset has departed point A at 10
AM. The time of transmission is illustrated as point B. Here, it
should be noted that the time reported (i.e., 10 AM) is not the
same as the time of the report (i.e., 10:15 AM).
[0037] After the transmission at point B, the asset stops at a rest
stop for 15 minutes. This 15-minute stop does not trigger an
arrival message because it has not met the user-configurable
no-motion time and sensitivity parameters of 30 minutes and 70%,
respectively. Specifically, the 15-minute stop has not met the 21
minute (i.e., 70% of 30 minutes) threshold dictated by the
user-configurable no-motion parameters.
[0038] At 12 AM the asset stops at point C in a yard. Even with the
repositioning of the asset within the yard for about 5 minutes, the
adaptive motion sensor determines that the asset has maintained a
no-motion condition for more than 70% of the 30 minutes. At the
expiration of the no-motion time, the mobile terminal then
transmits a message at 12:30 AM indicating that the asset had
stopped at 12 AM.
[0039] At 3 PM, the adaptive motion sensor determines that the
asset has entered a motion condition as the asset resumes its
journey. At 3:15 PM, the user-configurable motion time and
sensitivity parameters are met and the mobile terminal then
transmits a message at 3:15 PM indicating that the asset has
departed at 3 PM.
[0040] This process continues as the asset continues on to point E.
Throughout this process, the mobile terminal transmits start and
stop messages only when the user-configurable time and sensitivity
parameters are met. In one embodiment, the mobile terminal can also
be configured to periodically transmit status reports (e.g., once
per hour) when in a motion condition. These periodic status reports
would enable the system to track the asset while en route.
[0041] Arrival times, departures times, and code phase collections
are initiated by the adaptive motion sensor when the asset starts
and stops moving. In one embodiment, detection of when an asset
starts and stops moving is based on the change in measurable
vibration on the asset that is caused when an asset starts or stops
moving. The adaptive motion sensor can therefore be designed to
measure the amount of vibration or acceleration to determine
movement. Complications can arise when vibration or acceleration is
caused by other extraneous factors such as an engine running, or a
compressor or refrigeration unit running. The vibration from the
other sources can be detected by the sensor and can cause false
indications. The adaptive motion sensor can be designed to
differentiate between vibration resulting from true movement and
vibration resulting from extraneous sources. If it is assumed that
movement must come from a vehicle, and that the vehicle cannot move
unless an engine is running, then three states of motion can be
defined: (1) engine off, no movement; (2) engine on, no movement;
and (3) engine on, moving. There are other possible states such as
engine off and movement, but not valid. Also, state (2) may in fact
have two or more individual states from separate engines or motors
such as refrigeration units and compressors.
[0042] For simplicity, vibration from one or more engines can be
treated as one state. These three states will produce three
distinct levels of vibration in which the motion sensor can use to
determine movement. To determine these states the adaptive motion
sensor can collect and process data from a vibration sensor.
[0043] FIG. 3 illustrates an embodiment of a system that converts
vibration into a usable filtered number, which can be used to
determine the state of motion (e.g., moving or not-moving). In one
embodiment, vibration sensor 302 produces a voltage that is
proportional to the amount of acceleration or vibration. One such
device is an accelerometer-based MEMS (Micro-Electro-Mechanical
System) device, which can detect acceleration in two or three axis.
For detecting vibration, 2-axis is usually adequate.
[0044] Voltage from the accelerometer is then fed into A/D
converter 304. The output of A/D converter 304 produces a number
that is proportional to the amount of acceleration or vibration
measured by sensor 302. A low-speed A/D converter can be used to
convert a low-bandwidth (e.g., less than 50 hz) signal from an
analog voltage to a digital value. The system can be designed to
sample A/D converter 304 for a very short time at a very slow rate
(e.g., measure for a few milliseconds every five seconds) to
operate as an ultra-low power device. FIG. 4 shows example data
from a three-axis (x, y and z) accelerometer on an asset through
various states of movement from moving on the highway to no motion.
The values shown are the difference or derivative from consecutive
samples.
[0045] An accelerometer sensor detects acceleration on each of its
axis including that caused by gravity. The result is a constant DC
voltage from the axis that is affected by gravity. To detect
acceleration only from vibration and not gravity, the difference or
derivative is taken between consecutive samples to remove the DC
values and the effect from gravity and tilting of the sensor.
[0046] Vibration filter 306 smoothes the readings produced by A/D
converter 304 to reduce the variance from successive samples. Raw
A/D samples are processed in vibration filter 306 to produce a
smoother numeric value representing the level of vibration. In one
embodiment, a sample is taken every five seconds on each axis of
the accelerometer. The delta or difference between the new sample
and the last sample is then taken from the corresponding axis. The
deltas are integrated over six samples or every 30 seconds to
produce the filtered vibration value. Integration of the delta over
six samples has been found to have the most sensitivity to
vibration over other means of filtering such as a moving filter or
IIR filter. The chart in FIG. 5 shows the results from the
different filtering techniques from the raw data shown in FIG. 4.
The simple delta (in red) produced the largest and most usable
filtered vibration values.
[0047] Filtered vibration values are fed into adaptive threshold
stage 308 and motion detection stage 310. Based on the input
configuration parameters, motion detection stage 310 performs a
second level of filtering to determine the motion state. In one
embodiment, a motion state does not change unless the new motion
state is maintained for a configured percentage of time. This
assists in filtering out momentary or temporary changes in motion
state. Motion detection stage 310 compares the filtered vibration
value at its input to a threshold to determine the current sampled
motion state. If the new filtered vibration values are above the
threshold, motion detection stage 310 interprets the new reading as
"motion" and conversely, if below the threshold interprets the new
reading as "no-motion." It will then process these new raw input
values through the second stage filter to determine the current
motion state.
[0048] In one embodiment motion detection stage 310 is implemented
in software, which uses the filtered vibration inputs to determine
the current state of motion. FIG. 6 illustrates an example of the
various states of motion detection stage 310.
[0049] On initial power up the motion detector is in an unknown
state. The states are changed when motion detection stage 310
determines that criteria have been met for a motion or no-motion
state. The criteria is based on the filtered vibration input value,
the vibration threshold, the motion or no-motion times, and their
corresponding percentage.
[0050] To determine the current or next state, motion detection
stage 310 samples the filtered vibration input value at a uniform
rate and compares it to the vibration threshold. If the value is
above the threshold it will add "+1" to a motion integrator.
Conversely, if the value is below the vibration threshold, it will
add "-1", or subtract 1 from the motion integrator. If the motion
integrator integrates up to a positive threshold called the motion
integration threshold, it changes the state to "motion".
Conversely, if the motion integrator integrates down to a negative
threshold called the no-motion integration threshold, it changes
the state to "no-motion". From the "Unknown" state motion detection
stage 310 integrates values until it reaches either the motion or
no-motion integration threshold. FIG. 7 illustrates an example of
integration to a motion state.
[0051] As noted, the motion or no-motion integration thresholds are
based on a start time and stop time, and a start sensitivity and
stop sensitivity, respectively. These over-the-air configurable
parameters allow a user to specify what motion or no-motion means
in their own particular context. For example, a user can specify
that to change from a no-motion state to a motion state, the asset
must be in motion (moving) for at least 15 minutes, 70% of the
time. This means from the start of motion, the filtered vibration
values must stay above the threshold for the next 15 minutes 70% of
the time or for a total time of 15*0.7=10.5 minutes. This allows a
unit to survive brief stops such as at a traffic light after it has
truly started motion. For this example, when motion starts, a timer
also starts. When the timer reaches 15 minutes, if the integrated
value is above the threshold, the state will change to motion. The
integrated value is only reached if the unit stayed in motion for a
total of 10.5 minutes.
[0052] Adaptive threshold stage 308 inputs the same filtered
vibration values as motion detection stage 310 to automatically
adjust the threshold value to an optimum value for determining the
difference between "motion" and "no-motion." Adaptive threshold
stage 308 enhances the performance of motion detection stage 310
and eliminates the need for manual adjustment of the vibration
threshold. This results because the vibration characteristics can
vary from asset to asset in which the mobile terminal and the
adaptive motion sensor are installed. Also, the sensors themselves,
such as an accelerometer, can vary in sensitivity. For these
reasons, the vibration threshold may need to be different for each
sensor and asset for optimum performance. To avoid having to
manually adjust thresholds, adaptive threshold stage 308 collects
information about the vibration characteristics and uses this
information to automatically adjust the vibration threshold to an
optimum level for the particular sensor and asset.
[0053] As noted, in one embodiment, three valid states of motion
for an asset can be defined: (1) engine off, no movement; (2)
engine on, no movement; and (3) engine on, moving. Each of these
three states produces three distinct levels of the filtered
vibration values. Collected data can determine what these different
levels are and can be used to adjust the vibration threshold. In
one embodiment, the filtered vibration values are used to generate
a histogram.
[0054] FIG. 8 illustrates an example of a histogram generated from
the filtered vibration values from a motion sensor on an asset over
a period of time in which the asset has had many starts and stops.
State 1 data has been zeroed out since this data is not useful for
adjusting the threshold. Also, this data would dominate the
histogram since assets are typically not moving or stopped most of
the time. Essentially, the two useful states for adjusting the
threshold are states 2 and 3. To find the states that distinguish
motion and no-motion, the peaks are identified from right to left,
or from higher to lower vibration. This first peak from the right
represents the average level of vibration for an asset in state 3
(i.e., moving with engine or engines on). The next lowest peak (to
the left) in the histogram corresponds to state 2 (i.e., engine on,
not moving). Ideally, the vibration threshold should lie at the
null between the histogram peaks for states 2 and 3.
[0055] To find a good midpoint, the histogram is processed to find
the peaks. FIG. 9 illustrates an embodiment of the adaptive
threshold process. At step 902, the histogram is updated. Here,
filtered vibration values have a fixed range based on the gain from
the accelerometer sensor and the size of the A/D. The maximum
established range of the filtered vibration values can then be
divided into X number of ranges or bins of the histogram. As each
filtered vibration value enters this stage, the corresponding bin
or range is incremented. One bin is incremented for each new
filtered vibration value. To prevent overflow, the histogram scans
all bins for the highest peak. If an identified peak value is one
increment away from the maximum numeric bin value (e.g. 255 for
8-bits), then all bins can be scaled down by two to prevent
overflow. This essentially changes the histogram from an integrator
to a recursive filter for each bin. This means that the histogram
has a limited memory by retaining only the most recent values, and
can change or evolve as vibration characteristic change or
evolve.
[0056] Typically, assets and the adaptive motion sensor, are
stopped most of the time or are in state 1. Most of the filtered
vibration values fall in the lower bins of the histogram creating a
large peak. Since this information is not useful for adjusting the
threshold it is filtered out to prevent it from dominating the
histogram. A configurable vibration limit can be used to specify
the minimum filtered vibration that can be used in the histogram.
By doing this the histogram will only contain data from state 2 and
state 3. This data contains the information needed to adjust the
vibration threshold.
[0057] At step 904, the histogram is match filtered. It should be
noted, however, that before match filtering the raw histogram,
there should be a sufficient amount of data in the histogram. The
criteria to continue can be simply based on having a specified
minimum number of data points available. For example, the sum of
all the values in the histogram (energy) must exceed a specified
minimum value. This is better than simply testing the max value of
any bin.
[0058] Since the histogram may not have a smooth shape, some form
of filtering (e.g., match filtering) can be used to help find the
true peak. Match filters can work well when there is a know pattern
in the presence of noise. The known pattern in this case is one
caused by a constant vibration while in motion. This pattern will
look like a bell curve where the center is the average vibration
value. Momentary variations in vibration levels are cause by random
positions from the sensor, and from changes from the source of
vibration such as the road, the engine, etc. Over a long period of
time the vibration levels should average out to a bell curve. The
match filter coefficients can be modeled after the bell curve
produced under constant vibration from motion over a long period of
time.
[0059] FIG. 10 illustrates the raw histogram with the
match-filtered version below. The idea here is to center the filter
over each bin and multiply each point of the filter with each of
the corresponding bins about the center to get the filtered point
for that bin. The filter width can be limited to the significant
information for each peak. The resulting match filtered output is
smooth and should contain only one peak for each vibration
state.
[0060] At step 906, the peaks and nulls are found. This stage
processes the match-filtered histogram for the bin locations where
the state 2 and state 3 peaks are located as well as the bin where
the null or low point is between the two peaks. This information is
sent to the next stage to adjust the vibration threshold to the
ideal or optimum location at the null between the two peaks. The
null is where both bell curves, one from state 2 (engine on, no
movement) and one from state 3 (engine on, moving), overlap. This
is the location where the threshold will have the highest
probability of accurately distinguishing between moving and
not-moving.
[0061] At step 908, the threshold is updated. For each iteration of
the adaptive threshold process, the vibration threshold to motion
detection stage 310 is updated. The new threshold uses the bin
location of the null and the previous filtered value to produce the
new value using an IIR filter. The bin location of the state 2 and
state 3 peaks are not used to update the threshold, rather they are
used to qualify the result to ensure it does not track to an
erroneous value. The new threshold can be calculated using the
following equation: y(n)=k*y(n-1)+(1-k)*x(n) where, 0<=k<=1,
k is the IIR filter coefficient, x(n) is the bin location of the
null after processing a new match filtered histogram, y(n-1) is the
previous vibration threshold (in unit of bin numbers), and y(n) is
the new vibration threshold.
[0062] In one embodiment, before updating the vibration threshold,
a series of qualification tests can be made using configurable
parameters. Each of these checks or qualifiers should be passed in
order to update the vibration threshold. In addition to the limits,
each of these qualification tests can be enabled or disabled
independently over-the-air to provide maximum flexibility in
adjusting the algorithm over the air. A "Master Fail" bit will be
set if any of these enabled qualifiers fail. This bit can be sent
over the air to allow a quick tally of all units that are not
operating under normal parameters. From there, the failing unit can
be polled to extract the details of the failure which include which
qualifier failed, the match filtered histogram, vibration
threshold, etc. The intent of the qualifiers is to ensure that the
adaptive threshold process produces a threshold that improves
performance and does not degrade it. It is better to falsely fail a
qualifier and stop threshold adjustments than to adjust a threshold
based on incorrect data, and degrade performance.
[0063] These and other aspects of the present invention will become
apparent to those skilled in the art by a review of the preceding
detailed description. Although a number of salient features of the
present invention have been described above, the invention is
capable of other embodiments and of being practiced and carried out
in various ways that would be apparent to one of ordinary skill in
the art after reading the disclosed invention, therefore the above
description should not be considered to be exclusive of these other
embodiments. Also, it is to be understood that the phraseology and
terminology employed herein are for the purposes of description and
should not be regarded as limiting.
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