群智感知污染数据收集技术综述

摘要/Abstract

摘要： 传统的污染监测方法主要是通过固定基站进行监测的，但是这种方法缺乏灵活性且成本高昂，已不足以应对日益严重的污染问题。一种新的数据获取模式——移动群智感知为大范围感知数据提供了新思路。为了及时掌握移动群智感知收集污染数据的研究现状，本文对国内外现有研究进行系统全面的综述，并结合现有研究，为群智感知在智能手机上的应用提供可行方案。首先，对污染收集技术不同发展阶段问题进行总结；然后，对比分析不同众包污染收集系统的优缺点，并对所用的关键技术优缺点及适用场景进行说明；最后，对群智感知下收集污染数据存在的问题进行总结，并提出未来的研究重点。

关键词: 群智感知, 智能手机, 传感器;污染监测, 定位, 声音校准

Abstract: Traditional pollution monitoring methods are mainly carried out by fixed base stations, but these are inflexibility and expensive, which are no longer sufficient to deal with the problems of growing pollution. A new data acquisition mode—Mobile Crowdsensing—provides a new idea for large-scale data perception. In order to grasp the research status of pollution data collection of Mobile Crowdsensing in time, the existing researches at home and abroad are systematically and comprehensively reviewed, and feasible schemes are provided for the application of crowdsensing in smart phones based on the existing research. Firstly, the development stages of pollution collecting technology is elaborated. Then, the advantages and disadvantages of different crowd-sourced pollution collection systems are compared and analyzed, and the advantages and disadvantages of the key technologies used and the applicable scenarios are explained. Finally, the problems existing in the collection of pollution data under crowdsensing are summarized, and the future research focus is prospected.

Key words: crowdsensing, smartphone, sensor, pollution monitoring, positioning, sound calibration

曹升国, 王胜奥, 耿姝萌. 群智感知污染数据收集技术综述[J]. 计算机与现代化, 2022, 0(02): 70-78.

CAO Sheng-guo, WANG Sheng-ao, GENG Shu-meng. Review of Crowdsensing of Pollution Data Collection Technology[J]. Computer and Modernization, 2022, 0(02): 70-78.

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