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Using an Internet of Behaviours to Study How Air Pollution Can Affect People’s Activities of Daily Living: A Case Study of Beijing, China

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IoT Laboratory, School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK
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School of Earth Sciences and Engineering, Hohai University, Nanjing 211000, China
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College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
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State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Academic Editor: Francisco Florez-Revuelta
Sensors 2021, 21(16), 5569; https://doi.org/10.3390/s21165569
Received: 26 July 2021 / Revised: 10 August 2021 / Accepted: 16 August 2021 / Published: 18 August 2021
(This article belongs to the Section Internet of Things)
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. View Full-Text
Keywords: internet of things; internet of behaviours; air pollution; air quality index (AQI); PM2.5; people’s activities of daily living internet of things; internet of behaviours; air pollution; air quality index (AQI); PM2.5; people’s activities of daily living
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MDPI and ACS Style

Zhang, G.; Poslad, S.; Rui, X.; Yu, G.; Fan, Y.; Song, X.; Li, R. 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 2021, 21, 5569. https://doi.org/10.3390/s21165569

AMA Style

Zhang G, Poslad S, Rui X, Yu G, Fan Y, Song X, Li R. 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. 2021; 21(16):5569. https://doi.org/10.3390/s21165569

Chicago/Turabian Style

Zhang, Guangyuan, Stefan Poslad, Xiaoping Rui, Guangxia Yu, Yonglei Fan, Xianfeng Song, and Runkui Li. 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, no. 16: 5569. https://doi.org/10.3390/s21165569

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