CN110411460B

CN110411460B - Method and system for adaptively controlling tracking device

Info

Publication number: CN110411460B
Application number: CN201910339344.8A
Authority: CN
Inventors: 王辰宇; 万美玲; 李璟希
Original assignee: Gaoshu Anfu Hangzhou Technology Co ltd
Current assignee: Gaoshu Anfu Hangzhou Technology Co ltd
Priority date: 2018-04-27
Filing date: 2019-04-25
Publication date: 2021-08-27
Anticipated expiration: 2039-04-25
Also published as: CN110411460A

Abstract

Methods, systems, and apparatus are disclosed for adaptively controlling a tradeoff between positioning computation accuracy and power consumption of a mobile device. A method includes receiving a predetermined set of tasks of a subject or device associated with a mobile device, selectively activating a plurality of sensors of the mobile device based on the predetermined set of tasks, estimating a location of the mobile device by one or more of the selectively activated plurality of sensors of the mobile device, sensing information of the mobile device by the plurality of selectively activated sensors, and selecting a condition of the subject or device based on the estimated location, the predetermined set of tasks, and the sensing information of the plurality of selectively activated sensors.

Description

Method and system for adaptively controlling tracking device

Related patent application

The present patent application claims priority to U.S. provisional patent application No.62/663,365 filed on day 27, 4/2018, which is also a partial continuation of U.S. patent application No.15/978,346 filed on day 14, 5/2018, which claims priority to provisional patent application No.62/509,589 filed on day 22, 5/2017, all of which are incorporated herein by reference.

Technical Field

The described embodiments relate generally to location-based services. More particularly, the described embodiments relate to methods, systems and apparatus for adaptively controlling a trade-off between positioning calculation accuracy and power consumption of a mobile device that operates to select a subject (subject) or a condition (condition) of the device.

Background

Tracking and monitoring of goods and personnel is difficult. Available methods require a trade-off between the accuracy of the devices used for tracking and monitoring and the power consumed by the devices used for tracking and monitoring. It would be desirable to have methods, systems, and apparatus for adaptively controlling the tradeoff between positioning calculation accuracy and power consumption of a mobile device that operates to select a subject or condition of the device.

Disclosure of Invention

Embodiments include a method of adaptively controlling a tradeoff between positioning computation accuracy and power consumption of a mobile device. The method includes receiving a predetermined set of tasks of a subject or device associated with the mobile device, selectively activating a plurality of sensors of the mobile device based on the predetermined set of tasks, estimating a location of the mobile device by one or more of the selectively activated plurality of sensors of the mobile device, sensing information of the mobile device by the plurality of selectively activated sensors, and selecting a condition of the subject or device based on the estimated location, the predetermined set of tasks, and the sensing information of the plurality of selectively activated sensors.

Embodiments include a system for adaptively controlling a tradeoff between positioning computation accuracy and power consumption of a mobile device. The system includes a mobile device connectable to an upstream server. The mobile device operates to receive a predetermined set of tasks for a subject or device associated with the mobile device, selectively activate a plurality of sensors of the mobile device based on the predetermined set of tasks, estimate a location of the mobile device by one or more of the selectively activated plurality of sensors of the mobile device, and sense information of the mobile device by the plurality of selectively activated sensors. Further, at least one of the mobile device or the upstream server is operable to select a condition of the subject or the device based on the estimated location, the predetermined set of tasks, and the sensed information of the plurality of selectively activated sensors.

Other aspects and advantages of the described embodiments will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating by way of example the principles of the described embodiments.

Drawings

Fig. 1 illustrates several subjects/devices associated with a mobile device, where the mobile device operates to select the status of its corresponding associated subject/device, in accordance with an embodiment.

Fig. 2 is a flow chart comprising steps of a method of adaptively controlling a trade-off between accuracy of a positioning calculation and power consumption of a mobile device, according to an embodiment.

Fig. 3A, 3B illustrate a tracking device being transported, where the tracking device tracks a location while the tracking device is being transported, according to an embodiment.

Fig. 4A, 4B, 4C illustrate the operation of a tracking device according to an embodiment.

Fig. 5A, 5B illustrate a characterization process of a tracking device according to an embodiment.

FIG. 6 is a flow diagram of steps of a method including a location tracking device, according to an embodiment.

FIG. 7 is a block diagram of a location tracking device according to an embodiment.

Fig. 8 illustrates a tracking device being transported, where the tracking device tracks a location while the tracking device is being transported, and the tracking device reports a status of an object associated with the tracking device, according to an embodiment.

Fig. 9 illustrates an example of a mobile device (tracking device) operable in accordance with the disclosed embodiments of the embodiments.

Detailed Description

Described embodiments include methods, apparatuses, and systems for adaptively controlling a tradeoff between positioning computation accuracy and power consumption of a mobile device that operates to select a subject or a condition of the device. For an embodiment, the selection of the condition is based at least in part on tracking of the location of the subject or device.

Fig. 1 shows several bodies/

devices

111, 112, 113, 114, 115. Each of the bodies/

devices

111, 112, 113, 114, 115 has a corresponding associated

mobile device

121, 122, 123, 124, 125. The

mobile devices

121, 122, 123, 124, 125 operate to select the condition of their corresponding associated subjects/

devices

111, 112, 113, 114, 115. In operating to select the condition of its associated subject/device, the mobile device adaptively controls a tradeoff between positioning calculation accuracy and power consumption of the mobile device.

For an embodiment, mobile device 121 operates to receive a predetermined set of tasks for a principal/device 111 associated with mobile device 121. The mobile device 121 is further operative to selectively activate a plurality of sensors of the mobile device 121 based on the predetermined set of tasks. Further, the location of the mobile device 121 is estimated by one or more sensors of the plurality of selectively activated sensors of the mobile device 121. Once activated, the sensed information of the mobile device 121 is sensed by a plurality of selectively activated sensors. Mobile device 121 or upstream network 160 (or a combination of mobile device 121 and an upstream network) operates to select a condition of object/device 111 based on the estimated location, the predetermined set of tasks, and the sensed information in the plurality of selectively activated sensors.

As previously described, and as shown in fig. 1, each of the plurality of

mobile devices

121, 122, 123, 124, 125 operates to select the status of its corresponding associated principal/

device

111, 112, 113, 114, 115. Thus, for an embodiment, the status of one or more of the plurality of principals/

devices

111, 112, 113, 114, 115 is selected by the plurality of

mobile devices

121, 122, 123, 124, 125, or by the plurality of

mobile devices

121, 122, 123, 124, 125 in conjunction with the upstream server 140, or by the upstream server 140 based on information received from the plurality of

mobile devices

121, 122, 123, 124, 125.

For at least some embodiments, the plurality of

mobile devices

121, 122, 123, 124, 125 further monitor and coordinate each of the plurality of subjects or the plurality of devices. For at least some embodiments, monitoring and coordinating of subjects/devices includes monitoring and coordinating prisoners or psychiatric patients staying in a controlled area (e.g., safe area 130) and unable to escape. The sensors may include absolute (GPS) coordinates for outdoor tracking, and relative (e.g., beacons with accurately known locations relative thereto) coordinates for indoor location tracking. Further, for at least some embodiments, monitoring and coordinating subjects/devices includes monitoring and coordinating vehicles to stay on the track as planned. Further, for at least some embodiments, monitoring and coordinating the subject/device includes monitoring and coordinating the lifting or moving of boxed or palletised goods by authorized personnel or machines.

Embodiments include a system (such as formed by

mobile devices

121, 122, 123, 124, 125, and/or network 160, and/or upstream server 140) that includes a network of heterogeneous devices that can coordinate among themselves (in a master-slave mode or a peer-to-peer mode) to monitor and communicate the location and status of each principal/device in order to provide monitoring of certain principal/devices to a group of end users.

For at least some embodiments, the monitored subjects/

devices

111, 112, 113, 114, 115 include machines or devices managed by property management logistics (e.g., containers, generators, expensive minerals/resources) or persons in need of monitoring (e.g., workers for safety concerns, outdoor prisoners, or patients treated with medications), or high value animals and live stock.

At least some embodiments further include reporting the condition of the subject or device, including determining whether the subject or device successfully performed a particular set of tasks, including reporting whether the subject or device is safe, whether the subject or device is safe and on time, whether the subject or device is still within control. For at least some embodiments, data for each subject/device is monitored and collected to determine the condition of the subject in order to determine whether the subject successfully performed certain tasks. For particular embodiments, this includes a binary decision task to reduce data exchange between the user and the subject. Examples include whether the subject is in a safe environment, whether the subject is on schedule, whether the subject is still in or within a controlled area.

At least some embodiments include reporting the status of a subject or device to a user by presenting the subject/device status to end user 150 as shown. Additionally, at least some embodiments further include receiving feedback from the user regarding the accuracy of the selected condition and determining a false positive identification of the reported condition of the subject or device. An exemplary list is shown in fig. 1, which includes sub/dev1 OK, sub/dev2 OK-, and Feedback (FB) from the end user indicating that the OK status of sub/dev2 is yes, indicating that the OK status is correct, sub/dev3 OK, sub/dev4 OK-, and Feedback (FB) from the end user indicating that the OK status of sub/dev4 is yes, indicating that the OK status is correct, sub/dev5 OK-, and Feedback (FB) from the end user indicating that the OK status of sub/dev4 is no, indicating that the OK status is incorrect.

For at least some embodiments, as shown in fig. 1, false positive identification is included from human verification (e.g., observed from a command center or from a master device capable of verifying and recording ground truth). To improve overall detection accuracy, separate tools and systems are also required to allow false negative observations. For an embodiment, a group of users may provide feedback for a mobile device and consider both false positives/false negatives. True positives may be sampled to improve overall system detection accuracy.

At least some embodiments include each mobile device selecting a power mode for determining which of a plurality of sensors of the mobile device to activate. For at least some embodiments, the power modes include a sleep mode, a medium power mode, and a high power mode, and wherein the mobile device cycles through the power modes. For at least some embodiments, at least one mobile device persistently records and reports its status and location, and will cycle through the following states:

1. a sleep mode: motion sensor + wireless signature record. The system can go to sleep (turn on low power, time inaccurate timer, turn off high power, time accurate timer).

The goal is to save as much power as possible.

2. Medium power mode, motion shows the subject moving or the wireless signature changed (subject changing position or someone/something approaching the subject). The system wakes up from the sleep state (the low-power timer with poor time accuracy is closed, and the high-power timer with good time accuracy is started). Collect more data (motion with more samples + wireless) and trigger network location or even short term GPS (if available). The goal is to check whether it should go into high power mode or go back to sleep mode.

3. High power mode, performing certain tasks. For example, GPS is turned on for a period of time and the location data is submitted to a server for point of interest (POI) detection. Or turning the sonar/radar to observe the surrounding environment, detect an approaching object or check the moving state of the body. After the task is completed (e.g., an acknowledgement is obtained from the server), it will return to the low power mode to sleep.

At least some embodiments further include detecting the location of the subject/device based on the estimated location, the condition of the subject/device, and the sensed information of the corresponding plurality of selectively activated sensors of the mobile device. In particular, at least some embodiments include tracking and/or monitoring the location of a mobile device operating as a tracking device for tracking the location of a subject/device. For certain embodiments, the tracking device tracks the progress of a transport vehicle, such as a rail vehicle or vessel traveling along a rail or along a river.

At least some embodiments further include reselecting which of a plurality of sensors of the mobile device is activated based on a condition of the device.

For at least some embodiments, selectively activating the plurality of sensors of the mobile device includes selecting a sampling rate of one or more sensors of the plurality of selectively activated sensors. For at least some embodiments, estimating the location of the mobile device by one or more of the selectively activated plurality of sensors of the mobile device comprises: the position is estimated at a rate set by the sampling rate.

At least some embodiments further include ignoring the possibility that the subject or device is in a condition that is not on the predetermined set of tasks.

At least some embodiments further include selecting a condition of the subject or device based on the sensed acceleration, magnetic field, received RF signal (WiFi), received GPS signal, or rotation of the mobile device.

At least some embodiments further include dynamically updating the selected sensing information based on the condition of the subject or the device.

At least some embodiments further include determining one or more locations of the mobile device based on the condition of the subject or the device.

At least some embodiments further include monitoring how long a subject or device is operating in one or more tasks of a predetermined set of tasks. At least some embodiments further include presenting to an operator or user a sequence of one or more tasks monitored in a predetermined set of tasks for a subject or device.

For at least some embodiments, the task includes a condition of the subject or the device.

Fig. 2 is a flow chart comprising steps of a method of adaptively controlling a trade-off between accuracy of a positioning calculation and power consumption of a mobile device, according to an embodiment. A first step 210 includes receiving a predetermined set of tasks for a subject or device associated with a mobile device. A second step 220 includes selectively activating a plurality of sensors of the mobile device based on the predetermined set of tasks. A third step 230 includes estimating a location of the mobile device by one or more of the selectively activated plurality of sensors of the mobile device. A fourth step 240 includes sensing information of the mobile device by a plurality of selectively activated sensors. A fifth step 250 includes selecting a condition of the subject or device based on the estimated location, the predetermined set of tasks, and the sensed information of the plurality of selectively activated sensors.

For at least some embodiments, the predetermined tasks include one or more of: checking that a body or object (machine, worker, or material/supply) associated with a mobile device is in a safe absolute or relative position (an absolute position may include latitude/longitude, altitude (or no altitude) coordinates, and a relative position may include x, y, z (or no z) inside a structure/building), checking that a body or object associated with a mobile device has a movement condition, and determining whether it is in a safe movement condition (a safe movement condition may include moving with a driving vehicle, a potentially unsafe movement condition includes the body being lifted or rotated, or the body condition being open (a sealed box is open)), determining whether the body is moving with a vehicle, and checking that the body travel trajectory is as normal, checking that the body's natural environment is safe (e.g., temperature, humidity, or other suitable for example, humidity, brightness or humidity), checks whether the subject is in an unnatural environment, checks whether a person or machine moves/lifts the subject, and if so, checks whether the person or machine is authorized, checks whether the subject is under control, and acts on a predetermined schedule.

For at least some embodiments, the subject or device being monitored or tracked by the mobile device (or tracking device) includes one or more machines without self-moving capability, such as diesel or gasoline generators, power tools, vehicle trailers, boxed or palletized goods (such as raw materials, semi-finished goods), vehicles (machines with self-moving capability), such as truck-based construction machinery, delivery trucks, humans (such as construction workers for safety, outdoor prisoners, mental handicapped patients), expensive animals, such as for commercial use or environmental purposes.

For at least some embodiments, the condition of the subject or device includes one or more of: determining if no one would steal it, no one would injure or harm it, whether the prisoner or psychiatric left in the controlled area and could not flee, determining if the animal left in the controlled area.

At least some embodiments include selecting a condition of a plurality of subjects or a plurality of devices, wherein each of the plurality of subjects or the plurality of devices is associated with one of a plurality of mobile devices, and each of the plurality of subjects or the plurality of devices is monitored and coordinated by the plurality of mobile devices. For at least some embodiments, the monitoring and coordinating includes at least one of: monitoring and controlling prisoners or psychiatric patients remaining in the controlled area and unable to escape (this may include absolute coordinates (GPS) for outdoor tracking and relative (e.g., beacon with a known precise location relative thereto) coordinates for indoor location tracking), monitoring and coordinating vehicle stopping on the track as planned, monitoring and coordinating the lifting or moving of boxed or palletised cargo by authorized personnel or machines.

At least some embodiments further include reporting the condition of the subject or device, including determining whether the subject or device successfully performed a particular set of tasks, including reporting whether the subject or device is safe, whether the subject or device is safe and on time, whether the subject or device is still within control. For an embodiment, location and motion data is collected to estimate the behavior of the smartphone user (where he/she is and what is doing). With this system, data is monitored and collected to determine the subject's condition in order to determine whether the subject successfully performed certain tasks (specifically, these are binary decision tasks in order to reduce data exchange between the user and the subject). Some examples include determining whether the subject is in a safe environment, whether the subject is on time, and whether the subject is still within the controlled area.

At least some embodiments further include reporting a condition of the subject or device, receiving feedback from the user regarding an accuracy of the selected condition, and determining a false positive identification of the reported condition of the subject or device. At least some embodiments include false positive identification from human verification (e.g., observed from a command center or information processing capable host). At least some embodiments include separate tools and systems for allowing false negative observations to improve overall detection accuracy. At least some embodiments include a group of users providing feedback for the device and taking into account both false positives/negatives, and sampling from true positives in order to improve overall system detection accuracy.

Fig. 3A, 3B illustrate a tracking (mobile) device 320 being transported, wherein the tracking device 320 tracks location while the tracking device 320 is transporting, according to an embodiment. As shown, the tracking device 320 resides on the transportation device 310 (such as a rail car traveling on rails 380) while the tracking device 320 is in transit. As the tracking device 320 is in transit, the wireless receiver of the tracking device 320 receives wireless signals from the

base stations

340, 350 via

wireless transmissions

360, 370.

For an embodiment, the tracking device 320 measures the signal quality of the received signal as it travels in the direction of travel 330. In addition, the wireless signals include information that allows the tracking device 320 to identify which base station transmitted the received wireless signal. Based on the signal quality of the received signal and identifying which base station transmitted the received wireless signal, the location of the tracking device can be estimated. For example, the distance between the

base stations

340, 350 and the tracking device 320 may be estimated based on the received signal strength of the received wireless signals. That is, the amount of attenuation of the wireless signal transmitted during propagation between the base station and the tracking device provides an indication of the distance traveled by the wireless signal. Furthermore, the identification of the base station allows access to the location of the base station. One or more locations of the tracking device may be estimated based on the location of the base station and the estimated distance between the base station and the tracking device 320.

At least some embodiments further include improving the position estimate of the tracking device by limiting the tracking device to one-dimensional or near one-dimensional transportation. For example, railway travel is limited to travel on railroad tracks.

Fig. 3B shows vessel 312 on river 382, according to an embodiment, vessel 312 being constrained to travel up and down river 382. Also, rivers provide a nearly one-dimensional travel pattern. Thus, a power saving mode of operation of the tracking device 320 may be utilized.

Fig. 4A, 4B, 4C illustrate the operation of a tracking device according to an embodiment. Specifically, fig. 4A, 4B, 4C show the tracking device 320 at three different locations as it travels on the rail 380 over the railway vehicle 310. FIG. 4A shows a case where the distance between the tracking device 320 and the base station 340 is d1 and the distance between the tracking device 320 and the base station 350 is d 2. FIG. 4B shows a case where the distance between the tracking device 320 and the base station 340 is d3 and the distance between the tracking device 320 and the base station 350 is d 4. FIG. 4C shows a case where the distance between the tracking device 320 and the base station 340 is d5 and the distance between the tracking device 320 and the base station 350 is d 6.

For an embodiment, the receiver of the tracking device samples the received wireless signal at least three times after sensing the motion of the object. Sampling begins after motion is sensed because if no motion is sensed, there is no reason to sample multiple times because the tracking device is not in motion, and additional information sampling does not provide any additional information that may be used to track the position of the position tracking device.

The reason for using at least three information samples is described in fig. 4A, 4B, 4C. Specifically, the first position determination may be made based on the distances d1, d2 determined in FIG. 4A. The second position determination may be made based on the distances d3, d4 determined in fig. 4B. A third position determination may be made based on the determined distances d5, d 6.

Fig. 5A, 5B illustrate a characterization process of a tracking device according to an embodiment. As shown, the high power position determination device 520 is used to determine a calibration or characterization of the wireless signals received by the tracking device while traveling along a one-dimensional travel path, such as along a railway or along a river. Calibration is obtained by monitoring and storing the quality of the wireless signals received from the plurality of

base stations

522, 524, 526, 528 along the transmit path.

The high power position determining device 520 includes a precision position determining device (such as a GPS receiver) that determines a precise report of the position of the high power position determining device 520 when the high power position determining device 520 also receives the wireless signal in transmission. Fig. 5B shows the received signal power of the wireless signals received from each of the

base stations

522, 524, 526, 528 as the high power position determining device 520 changes along the transportation path. By storing the precise location and quality characteristics of the wireless signals received from the

base stations

522, 524, 526, 528 at each of a number of different locations, the location of the tracking device may be later estimated based on the signal quality of the wireless signals received by the tracking device. For example, at the sampling point 592 of the received signal power, the wireless signals received from each of the

base stations

522, 524, 526, 528 may be measured and the corresponding accurate position estimate stored. If at a later time, different position tracking devices measure received signals having the same received signal quality (such as received signal power), the position tracking device can be estimated by retrieving stored positions for various received signal powers. A second sampling point 594 shows a different set of received signal powers and corresponding locations (locations on the track 380). Also, as shown, a location on the track has a corresponding set of received signal powers. Sampling points can be obtained along the track where the received signal power (or other received signal quality) and corresponding position are measured. As described above, for embodiments, another device may later measure the same received signal quality and then estimate its location based on comparing the measured received signal quality to a previously stored signal quality and corresponding stored location.

FIG. 6 is a flow diagram of steps of a method including a location tracking device, according to an embodiment. A first step 610 includes receiving, by a receiver of a tracking device attached to an object, wireless signals from a plurality of base stations, wherein the wireless signals include information for each of the plurality of base stations that transmitted the corresponding wireless signals. A second step 620 includes sensing, by the receiver, motion of the object. A third step 630 includes sampling the received wireless signal at least three times by the receiver after sensing the motion of the object. A fourth step 640 includes estimating a plurality of positions of the receiver based on signal characteristics of the information samples of the received wireless signals, information of the plurality of base stations, and predetermined knowledge of the mode of transportation of the object being transported.

For at least some embodiments, the mode of transport limits the plurality of locations to one dimension. This condition allows for better power usage versus accuracy of the position determination. For an embodiment, the predetermined knowledge of the mode of transportation includes specifying the mode of transportation as a railway or a waterway. That is, the railroad is only allowed to travel along the rails. This limits the freedom of movement of the object to which the tracking device is attached. Thus, the predetermined course of the rails may be utilized to enhance the accuracy of location determination and tracking.

At least some embodiments further include identifying a condition of the mode of transportation of the object based on the estimated location of the receiver. The condition may include the object moving too slowly or too fast. Further, the condition may include a task or other condition of the subject.

For at least some embodiments, wireless signals are received from a plurality of base stations over a first wireless network, and further comprising transmitting, by a tracking device, information related to the identified condition over a second wireless network. That is, the wireless signals received by the tracking device may be transmitted by any type of network including the base station transmitting the wireless signals. The first wireless network may include base stations dedicated only to transmitting signals for providing location determination. Alternatively or additionally, the first wireless network may comprise another wireless communication system. The second wireless network may include a communication wireless network, such as a cellular wireless network, a WiFi network, a bluetooth network, an ultrasonic network, or a radar network. The second wireless network provides upstream data communication, wherein the upstream data communication may include a condition of the object.

At least some embodiments further include calibrating the signals received while traveling along the railroad. For an embodiment, this includes transporting a high power, high accuracy position determining device along a railway, monitoring characteristics of the received wireless signals, and storing a plurality of locations of the high power, high accuracy position determining device and associated monitored characteristics of the received wireless signals for each of the plurality of locations.

For at least some embodiments, estimating a plurality of locations of a receiver based on signal characteristics of information samples of the received wireless signals, information of a plurality of base stations, and predetermined knowledge of a mode of transport of the object being transmitted further comprises: for each of a plurality of locations, retrieving monitoring characteristics of the received wireless signals, comparing the retrieved monitoring characteristics of the received wireless signals for each of the plurality of locations with the received wireless signals from the plurality of base stations, and further estimating the plurality of locations of the receiver based on the comparison between the retrieved monitoring characteristics of the received wireless signals for each of the plurality of locations and the received wireless signals from the plurality of base stations.

Fig. 7 is a block diagram of a location tracking device 700 according to an embodiment. As shown, the tracking device 700 includes a first radio (radio 1)720 that receives wireless signals from a base station, such as the base station A, B, C previously described. The signal quality (such as received signal strength) of the received wireless signal is measured.

The location tracking device 700 includes a CPU 710. For an embodiment, the CPU 710 receives measurements from the first radio 720 and estimates the position of the position tracking device 700 based on signal characteristics of information samples of the received wireless signals, information of a plurality of base stations, and predetermined knowledge about the mode of transportation of the object being transported.

For an embodiment, CPU 710 may additionally determine a status of an object associated with the tracking device based at least in part on the determined location of the object.

For an embodiment, CPU 710 may additionally determine a location of an object associated with the tracking device based at least in part on the determined location or the sensed motion of the object.

For an embodiment, the position tracking device 700 further includes a motion sensor 740 for detecting motion of the tracking device 700 and the object. If it is sensed that the object is moving, only position tracking needs to be performed.

For an embodiment, the tracking device 700 includes a memory 752 in which a representation of the received wireless signal may be stored. The tracking device 800 may utilize the characterization to improve location tracking.

For an embodiment, the location tracking device 700 further includes a second radio (radio 2) 725. The second radio 725 allows the tracking device 700 to download the characterization. Further, the second radio 725 allows the tracking device 700 to upload the status of the object associated with the tracking device 700. For an embodiment, the functions of the first radio and the second radio are comprised in a single radio. For an embodiment, the second radio 725 wirelessly connects to the upstream server 750 over a first wireless network (network 1)772, where received signal representations (such as the previous representations shown in fig. 5A, 5B) are downloaded, and the status of the object associated with the tracking device is uploaded.

Further, for an embodiment, first radio (radio 1)720 receives wireless signals over second network (network 2)774, which second network (network 2)774 includes, for example, base station A, B, C.

Fig. 8 illustrates a tracking device 320 being transported, where the tracking device 320 tracks a location while the tracking device 320 is transporting, and the tracking device reports a status of an object associated with the tracking device, according to an embodiment.

As shown, for the embodiment, the tracking device 320 receives wireless signals via

wireless transmissions

360, 370 from

wireless base stations

340, 350 over a first network 892. For an embodiment, the tracking device 320 then tracks the location of the tracking device 320 and determines a condition of an object or device associated with the tracking device based at least in part on the tracked location. Further, the tracking device communicates the status of the object or device to the cloud server 896 over the second network 894. For the embodiment, the second network 894 is a wireless network that is a different network than the first network 892. For the embodiment, they are the same network.

Fig. 9 illustrates an example of a mobile device (tracking device) operable in accordance with the disclosed embodiments of the embodiments. For an embodiment, user location data is continuously collected from the mobile device over time. The data may include multiple sensor data streams with time stamps.

The spatial information of the user (such as longitude, latitude, altitude) may be determined by a location sensing system, such as Global Positioning System (GPS)920 and/or a network-based location, such as a location determined by a cellular and/or WiFi network of mobile (tracking) device 900 as previously described. Based on the spatial information, controller 910 of mobile device 900 (or another controller connected to controller 910) can roughly determine the user's location. However, GPS may be limited because the exact location or actual merchant (point of interest) visited by the user may not be determinable from GPS alone. Embodiments provide alternative or additional location information determined by the controller 910 or a controller that may be electronically connected to the controller 910.

The signals sensed by the motion sensor (e.g., accelerometer) 940 may be used to provide additional user-related information. That is, for example, the GPS 920 may be sufficiently accurateTo narrow the identification of the location of interest of the three merchants. The signal generated by the motion sensor 940 may provide an indication of user activity, which may be used to additionally identify a location of interest. For example, when the department store (e.g. department store)

) Located in a coffee shop (e.g. coffee shop)

) While aside, the user's motion pattern may be used to disambiguate between the two points of interest Wallmar and Starbucks. If the user's movement pattern indicates that the user is walking most of the time, the user has a higher probability of visiting a department store. On the other hand, if the user's motion pattern indicates that the user is sitting still for a large portion of the time, the probability of the user accessing the cafe is higher.

Images captured by camera 930 of mobile device 900 may be used to provide additional user-related information. That is, for example, the identity of a merchant near the user's location may be used to determine a point of interest.

Audio signals sensed by microphone 950 of mobile device 900 can be used to provide additional user-related information. That is, for example, loud and quiet noise in the background of the user's location may be used to help determine the point of interest. For example, because the noise level in a library is generally low, if the noise level is low, the probability of the user being in the library is higher than the probability of the user being in a restaurant.

The user's direction may be determined by, for example, compass 970 of mobile device 900. Compass 970 may provide a current or historical direction of the user. The user's indication may be used to help determine the point of interest.

The user's rotation may be determined by, for example, gyroscope 972 of mobile device 900. Gyroscope 972 may provide current or historical rotations of the mobile device carried by the user. The rotation of the user's mobile device may be used to help determine the point of interest.

The user's ambient temperature may be determined by, for example, thermometer 974 of mobile device 900. Thermometer 974 may provide a current or historical ambient temperature of the user. The temperature of the user may be used to help determine the point of interest. For example, the temperature may be used to determine whether the user is outdoors or indoors.

The user's exposure to ambient light may be determined by, for example, light sensor 976 of mobile device 900. Light sensor 976 may provide a current or historical exposure of the user. The user's exposure may be used to help determine the point of interest. For example, the sensed IR level may be used to determine whether the user's mobile device is, for example, in the user's pocket, and whether the user is in direct sunlight.

User input information may be received from a keyboard or touch screen 982. If the user can be inferred, based on a determination that the user is using input (keyboard or touch screen) behavior, and thus, an educated guess can be made about the user's location. For example, if the user is inputting information, the user may not be driving. If the user is speaking, the user may not be in a movie theater.

Barometric pressure information from barometric pressure sensor 984 may be sensed and used to determine user-related information. For example, barometric pressure information may be used to infer the height of the user, and thus, to determine at which floor of a building the user is currently located. GPS may be inaccurate inside buildings, and therefore, barometric pressure information may be very useful.

The network 990 to which the mobile device 900 is connected may provide additional user-related information. For example, a server 980 of the network may have a street view image that provides additional information about the approximate location where the user is located. The connection to the remote server 980 is optional, as the mobile device may be disconnected from the server. Additionally, a portion of the user profile 960 calculations may be performed on the mobile device and may not need to run on a server.

It should be appreciated that the processes of the described embodiments for adaptively controlling a tradeoff between positioning computation accuracy and power consumption of the mobile device 900 may occur at the controller 910, at the network server 980, or at a combination of both the controller 910 and the network server 980. Almost all tradeoffs between adaptively controlling the accuracy of location calculations and power consumption of a mobile device can occur at a network server 980 if the connection of the network 990 allows for the appropriate upload of location information and/or sensor information to the network server. However, if a connection to the network 990 is not available, at least a portion of the processing to adaptively control the tradeoff between positioning calculation accuracy and power consumption of the mobile device may occur at the controller 910 of the mobile device 900.

For at least some embodiments, one or more of the described combinations of sensing states of sensors (920, 930, 940, 950, 970, 972, 974, 976, 982, 984) and/or network connections (940) are used in a process for adaptively controlling a trade-off between positioning computation accuracy and power consumption of a mobile device. The sensing state of the sensor changes over time. For an embodiment, a pattern (pattern) or a series of patterns in one or more sensing states of the described sensor may be identified and/or recognized. For at least some embodiments, the change in style indicates that the user is arriving (start time) or leaving (end time) the point of interest, or that the user is staying at the user or transitioning between points of interest. Thus, for at least some embodiments, information of the sensed state of the sensor may be used to determine user dwell. For example, if the motion state (940) indicates that the user is stationary for a period of time, then for at least some embodiments, this is used to identify the period of time as a potential user dwell. If the network (940) is connected to the wireless station for a time period, then for at least some embodiments, this is used to identify the time period as a potential user dwell. This information may be used to indicate that the user is staying if the sensed light intensity of the light sensor 976 of the mobile device remains at a constant level (same) for a period of time. This information may be used to indicate that the user is staying if the sensed temperature remains at the same level for a period of time.

Although specific embodiments have been described and illustrated, the embodiments are not to be limited to the specific forms or arrangements of parts so described and illustrated.

Claims

1. A method of adaptively controlling a tradeoff between positioning computation accuracy and power consumption of a tracking device, comprising:

receiving a predetermined set of tasks for an object associated with the tracking device;

selectively activating a plurality of sensors of the tracking device based on the predetermined set of tasks;

estimating, by one or more sensors of the selectively activated plurality of sensors of the tracking device, a plurality of locations of the tracking device, comprising:

receiving, by a first radio of the tracking device attached to the object, wireless signals from a plurality of base stations of a first network, wherein the wireless signals include information of each of the plurality of base stations of the first network that transmitted the corresponding wireless signal;

sensing, by the tracking device, motion of the object;

sampling, by the tracking device, the received wireless signal at least three times in response to sensing motion of the object;

downloading, by a second radio of the tracking device, a representation of the wireless signal from a second network to the tracking device along a same transmission path, wherein the representation of the wireless signal was previously determined by a high power position monitoring device that previously measured and stored received wireless signal quality when receiving the wireless signal from the plurality of base stations while traveling along the same transmission path;

estimating the plurality of locations of the tracking device based on signal characteristics of information samples of wireless signals received from the plurality of base stations, the information of the plurality of base stations, and predetermined knowledge about a mode of transportation in which the object is being transported including the characterization of the wireless signals;

the method further comprises the following steps:

sensing, by the plurality of selectively activated sensors, sensed information of the tracking device; and

selecting a condition of the subject based on the estimated plurality of locations, the predetermined set of tasks, and the sensed information of the plurality of selectively activated sensors.

2. The method of claim 1, further comprising:

a status of selecting a plurality of objects, wherein each of the plurality of objects is associated with one of a plurality of tracking devices;

monitoring and coordinating, by the plurality of tracking devices, each of the plurality of objects.

3. The method of claim 1, further comprising reporting the condition of the subject, receiving feedback from a user regarding an accuracy of the selected condition, and determining a false positive identification of the reported condition of the subject.

4. The method of claim 1, further comprising selecting, by the tracking device, a power mode for determining which of the plurality of sensors of the tracking device are activated.

5. The method of claim 4, wherein the power modes include a sleep mode, a medium power mode, and a high power mode, and wherein the tracking device cycles through the power modes.

6. The method of claim 1, further comprising detecting a location of the subject based on the estimated location, the condition of the subject, and the sensed information of the plurality of selectively activated sensors.

7. The method of claim 1, further comprising:

reselecting which sensor of the plurality of sensors of the tracking device is activated based on the condition of the subject.

8. The method of claim 1, wherein selectively activating a plurality of sensors of the tracking device comprises: selecting a sampling rate for one or more sensors of the plurality of selectively activated sensors.

9. The method of claim 1, further comprising selecting the condition of the subject based on sensed acceleration, magnetic field, received RF signal (WiFi), received GPS signal, or rotation of the tracking device.

10. The method of claim 1, further comprising dynamically updating the selected sensing information based on the condition of the subject.

11. The method of claim 1, further comprising determining one or more locations of the tracking device based on the condition of the subject.

12. The method of claim 1, further comprising monitoring how long the object operates in one or more tasks of the predetermined set of tasks.

13. The method of claim 12, further comprising presenting to an operator of a user a sequence of one or more tasks monitored in the predetermined set of tasks of the subject.

14. The method of claim 1, wherein a task comprises a condition of the subject.

15. A system for adaptively controlling a tradeoff between positioning computation accuracy and power consumption of a tracking device, comprising:

a tracking device connectable to an upstream server, the tracking device operable to:

sensing, by the tracking device, motion of the object;

the tracking device is further operable to:

wherein at least one of the tracking device or the upstream server is operable to select a condition of the subject based on the estimated location, the predetermined set of tasks, and the sensed information of the plurality of selectively activated sensors.