城市空气质量感知方法综述  

Review on Urban Air Quality Perception Methods

作　　者：王鹏跃 郭茂祖 赵玲玲[3] 张昱 WANG Peng-yue;GUO Mao-zu;ZHAO Ling-ling;ZHANG Yu(School of Electrical and Information Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Key Laboratory of Intelligent Processing for Building Big Data,Beijing 100044,China;School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China;State Key Laboratory in China for GeoMechanics and Deep Underground Engineering,Beijing 100083,China)

机构地区：[1]北京建筑大学电气与信息工程学院,北京100044 [2]建筑大数据智能处理方法研究北京市重点实验室,北京100044 [3]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001 [4]深部岩土力学与地下工程国家重点实验室,北京100083

出　　处：《计算机科学》2019年第B06期35-40,51,共7页Computer Science

基　　金：国家自然科学基金(61502117);北京市教委科技计划重点项目(KZ201810016019);国家重点研发计划(2016YFC0600901);教育部产学研协同育人项目(201801113001);北京建筑大学市属高校基本科研业务费专项资金(X18197,X18198,X18203,X18018);北京建筑大学双塔计划优秀主讲教师(21082718041)资助

摘　　要：城市空气质量信息对于控制空气污染和保护大众健康都是尤为重要的。城市空气质量感知方法按传感器位置是否发生改变可划分为静态感知方法和动态感知方法两种。其中静态感知方法的数据是基于空气质量监测站、卫星遥感和固定位置的传感器进行采集的。再按成本高低可进一步划分为低成本静态感知和高成本静态感知。动态感知方法按是否以参与者为感知中心划分为参与式方法和非参与式方法。随着感知技术和计算能力的发展,将多源异构的城市数据,如气象数据、交通数据等进行融合,可进一步提高感知的准确性。文中首先对当前空气质量感知方法进行综述,然后分类介绍了各种方法的感知框架和数据处理方法,最后讨论了其面临的问题和挑战。Urban air quality information is especially important for controlling air pollution and protecting public health.According to whether the sensor position changes,urban air quality sensing methods can be divided into two methods:static perception methods and dynamic perception methods.The data acquisition of the static sensing method is based on air quality monitoring stations,satellite remote sensing and fixed position sensors.Then,the static sensing method is further divided into low-cost static sensing method and high-cost static sensing method.The dynamic sensing method can be divided into participatory method and non-participating method according to whether the participant is the perceptual center.With the development of sensing technology and computing ability,the fusion of multi-source hete-rogeneous urban data,such as meteorological data and traffic data,can further improve the accuracy of perception.This paper firstly summarized current air quality sensing methods,then classified the sensing framework and data processing methods of various methods,and finally discussed the problems and challenges.

关 键 词：空气污染 城市感知 数据采集 机器学习 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]