Method and apparatus of adaptive sampling for vehicular crowd sensing applications

US2016124976A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2016124976-A1
Application numberUS-201414531242-A
CountryUS
Kind codeA1
Filing dateNov 3, 2014
Priority dateNov 3, 2014
Publication dateMay 5, 2016
Grant date

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  5. First independent claim

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Abstract

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A crowd sensing system includes a central entity and remote entities. The remote entities receive queries from the central entity and transmit data to the central entity in response to the query. The sample data obtained from the queried remote entity is analyzed and an average value for the sample data is determined for a current time interval. The central entity determines whether a difference between the average values for the current time interval and a previous time interval is greater than a predetermined threshold. The central entity increases the number of entities in response to the difference being greater than the predetermined threshold, and decreases the respective number of remote entities sampled in response to the difference being less than the predetermined threshold. The central entity queries a number of remote entities in the plurality of regions equal to the adjusted number of samples identified by the central entity.

First claim

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What is claimed is: 1 . A method of adaptively controlling a sampling size for crowd sensing applications, the method comprising the steps of: (a) identifying a plurality of geographic regions for obtaining sample data; (b) identifying, by a central entity, a respective number of remote entities to sample within each geographical region during a current time interval; (c) obtaining sample data from each of the respective remote entities identified in step (b); (d) determining, by the central entity, a statistical value for the sampled data; (e) determining whether a difference between the statistical value for the current time interval and a statistical value for a previous time interval is greater than by a predetermined threshold; (f) increasing the respective number of remote entities sampled in the regions in response to the difference being greater than the predetermined threshold; otherwise, decreasing the respective number of remote entities sampled in the regions in response to the difference being less than the predetermined threshold; and (g) repeating steps (b)-(g) utilizing the respective number of entities to sample as identified in step (f). 2 . The method of claim 1 wherein obtaining sample data from each of the respective remote entities further comprises the steps of: transmitting a query requesting data from the central entity to each of the respective remote entities identified in step (b); and each of the queried remote entities transmitting data to a central entity in response to the query. 3 . The method of claim 2 wherein each respective remote entity queried is randomly selected from an entire population in each geographical region. 4 . The method of claim 3 wherein available remote entities from which to sample from is rotated periodically. 5 . The method of claim 3 wherein a respective remote entity interrogated in a previous sampling period is removed from a next sampling period. 6 . The method of claim 1 wherein the predetermined threshold identified in step (b) is a function of a predetermined percentage of the previous average value for the previous time interval. 7 . The method of claim 6 wherein the decision for determining whether the difference is greater than the predetermined threshold is represented by the following formula: | X T − X T-1 |≧α| X T-1 | where X T is the average value of the data received from the queried entities at the current time interval, X T-1 is the average value of the data received from the queried entities at the current time interval, and α is a predetermined percentage. 8 . The method of claim 1 wherein in response to decreasing the number sample, the number sample is selected from the minimum of either an upper threshold or the decreased number sample. 9 . The method of claim 1 wherein in response to increasing the number sample, the number sample is selected from the maximum of either a lower threshold or the decreased number sample. 10 . The method of claim 1 wherein in the statistical value is an average value. 11 . The method of claim 1 wherein the statistical value is determined by the central entity. 12 . A crowd sensing system comprising: a central entity including a processor, transmitter, and receiver identifying a plurality of geographic regions for obtaining sample data; a plurality of remote entities located in the plurality of geographical regions, the remote entities including a transmitter and receiver receiving queries from the central entity, the queried remote entities transmitting data to the central entity in response to the query; wherein the central entity identifies a respective number of remote entities within each region to obtain sample data, wherein sample data is obtained from each of the identified remote entities, wherein the central entity determines a statistical value for the sampled data, wherein the central entity determines whether a difference between the statistical value for the current time interval and a statistical value for a previous time interval is greater than a predetermined threshold, wherein the respective number of remote entities sampled in the region are increased in response to the difference being greater than the predetermined threshold; otherwise, decreasing the respective number of samples identified from the region in response to the difference being less than the predetermined threshold; and wherein the central entity queries a number of remote entities in the plurality of regions equal to the adjusted number of samples identified by the central entity during a next time interval. 13 . The method of claim 12 wherein the central entity obtaining sample data from each of the respective remote entities further comprises: the central entity transmitting a query requesting data from the central entity to each of the identified remote entities; and the queried entities transmitting data to a central entity in response to the query. 14 . The system of claim 13 wherein the remote entities queried by the central entity are randomly selected from an entire population in each geographical region. 15 . The system of claim 14 wherein available remote entities from which to sample from within each region is rotated periodically. 16 . The system of claim 14 wherein a respective remote entity queried in a previous sampling period is removed from a next sampling period. 17 . The system of claim 12 wherein the predetermined threshold is a function of a predetermined percentage of the previous average value for a previous time interval. 18 . The system of claim 17 wherein a decision for determining whether the difference is greater than the predetermined threshold is represented by the following formula: | X T − X T-1 |≧α| X T-1 | where X T is the average value of the data received from the queried remote entities at the current time interval, X T-1 is the average value of the data received from the queried remote entities at the current time interval, and α is a predetermined percentage. 19 . The system of claim 12 wherein in response to decreasing the number of remote entities sampled, the central entity selects the number of remote entities sampled from the minimum of either an upper threshold and the decreased number sample. 20 . The system of claim 12 wherein in response to increasing the number of remote entities sampled, the central entity selects the number of remote entities sampled from the maximum of either a lower threshold and the increased number sample.

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Classifications

  • where the source of the transmitted information selects which information to transmit to each vehicle · CPC title

  • Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences · CPC title

  • in relation to timing considerations · CPC title

  • H04L43/024Primary

    by adaptive sampling · CPC title

  • Location-based management or tracking services · CPC title

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What does patent US2016124976A1 cover?
A crowd sensing system includes a central entity and remote entities. The remote entities receive queries from the central entity and transmit data to the central entity in response to the query. The sample data obtained from the queried remote entity is analyzed and an average value for the sample data is determined for a current time interval. The central entity determines whether a differenc…
Who is the assignee on this patent?
Gm Global Tech Operations Inc
What technology area does this patent fall under?
Primary CPC classification H04L43/024. Mapped technology areas include Electricity.
When was this patent published?
Publication date Thu May 05 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).