A location information collection framework based on crowd sensing environment

Abstract

The invention discloses a position information acquisition frame based on crowd sensing environment. The position information acquisition frame is decoupled into a position information acquisition module, an environment monitoring module and a position data processing module, different positioning requirements can be achieved through configuration of different positioning parameters, and the positioning parameters comprise an acquisition frequency, a data acquisition mode and an equivalent state. Different data processing modes can be achieved through expansion of a custom data transmission service and configuration of a specific data transmission service and a specific RPC remote service address. Based on the crowd sensing environment, an adaptive acquisition mode can be performed according to current network environment, an adaptive adjustment processing mode and adaptive storage and transmission modes can be made aiming at a current network state, and the acquisition frame which can achieve high performance and a universal type from a fundamental level is provided.

Description

technical field [0001] The present invention relates to the field of location information collection in a crowd-sensing environment, in particular to a location information collection framework based on a crowd-sensing environment. Background technique [0002] Crowdsensing mines group information by perceiving individual information and reacts to individuals or groups. It is a cooperation and win-win situation between individuals and groups. The theme is "perception" and "mining". The perception layer is composed of individuals and smart devices they carry. The mining layer is supported by the background data server, and the sensors and applications complete the data collection and the feedback of the group perception results. With the current hot rise of wearable devices and the fast pace of modern social life, social software focuses on location services, and people's daily travel life will generate a large amount of location data information. With the rapid development ...

AI Technical Summary

Problems solved by technology

However, no one has proposed a complete high-performance location acquisition framework based on crowd sensing environment. Most of them only analyze the collected spatio-temporal data, but ignore the energy consumption and resource usage when collecting these spatio-temporal data. question

[0004] Generally, when collecting location information, the collection module is not divided vertically, and the location data collection service is combined with the data transmission service. The location data collection service task will cause the task blockage of the transmission service; for the location data collection method, there is no Dynamically adapt and adjust in a configurable manner; for the processing of collected data, adaptive processing cannot be performed in a diversified form; for the detection of the environmental status relied on in the process of collection and transmission, it needs to be repeated every time it is processed

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