Using an Internet of Behaviours to Study How Air Pollution Can Affect People's Activities of Daily Living: A Case Study of Beijing, China
文献类型：期刊论文
| 作者 | Zhang, Guangyuan3; Poslad, Stefan3; Rui, Xiaoping1; Yu, Guangxia3; Fan, Yonglei3; Song, Xianfeng4; Li, Runkui2,4 |
| 刊名 | SENSORS
 |
| 出版日期 | 2021-08-01 |
| 卷号 | 21期号:16页码:37 |
| 关键词 | internet of things internet of behaviours air pollution air quality index (AQI) PM2 5 people's activities of daily living |
| DOI | 10.3390/s21165569 |
| 通讯作者 | Rui, Xiaoping(ruixp@hhu.edu.cn) |
| 英文摘要 | This study aims to quantitatively model rather than to presuppose whether or not air pollution in Beijing (China) affects people's activities of daily living (ADLs) based on an Internet of Behaviours (IoB), in which IoT sensor data can signal environmental events that can change human behaviour on mass. Peoples' density distribution computed by call detail records (CDRs) and air quality data are used to build a fixed effect model (FEM) to analyse the influence of air pollution on four types of ADLs. The following four effects are discovered: Air pollution negatively impacts people going sightseeing in the afternoon; has a positive impact on people staying-in, in the morning and the middle of the day. Air pollution lowers people's desire to go to restaurants for lunch, but far less so in the evening. As air quality worsens, people tend to decrease their walking and cycling and tend to travel more by bus or subway. We also find a monotonically decreasing nonlinear relationship between air quality index and the average CDR-based distance for each person of two citizen groups that go walking or cycling. Our key and novel contributions are that we first define IoB as a ubiquitous concept. Based on this, we propose a methodology to better understand the link between bad air pollution events and citizens' activities of daily life. We applied this methodology in the first comprehensive study that provides quantitative evidence of the actual effect, not the presumed effect, that air pollution can significantly affect a wide range of citizens' activities of daily living. |
| WOS关键词 | WILLINGNESS-TO-PAY ; UNIT ROOTS ; PERFORMANCE ; EXPOSURE ; URBAN |
| 资助项目 | National Key Research and Development Program of China[2017YFB0503605] ; National Natural Science Foundation of China[41771478] ; Fundamental Research Funds for the Central Universities[2019B02514] ; Beijing Natural Science Foundation[8172046] ; China Scholarship Council (CSC) ; Queen Mary University of London |
| WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000689837900001 |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Beijing Natural Science Foundation ; China Scholarship Council (CSC) ; Queen Mary University of London |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/165233]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Rui, Xiaoping |
| 作者单位 | 1.Hohai Univ, Sch Earth Sci & Engn, Nanjing 211000, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Queen Mary Univ London, Sch Elect Engn & Comp Sci, IoT Lab, London E1 4NS, England 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Guangyuan,Poslad, Stefan,Rui, Xiaoping,et al. Using an Internet of Behaviours to Study How Air Pollution Can Affect People's Activities of Daily Living: A Case Study of Beijing, China[J]. SENSORS,2021,21(16):37. |
| APA | Zhang, Guangyuan.,Poslad, Stefan.,Rui, Xiaoping.,Yu, Guangxia.,Fan, Yonglei.,...&Li, Runkui.(2021).Using an Internet of Behaviours to Study How Air Pollution Can Affect People's Activities of Daily Living: A Case Study of Beijing, China.SENSORS,21(16),37. |
| MLA | Zhang, Guangyuan,et al."Using an Internet of Behaviours to Study How Air Pollution Can Affect People's Activities of Daily Living: A Case Study of Beijing, China".SENSORS 21.16(2021):37. |
入库方式： OAI收割
来源：地理科学与资源研究所
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