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Theses

Low-cost wireless sensor networks in participatory air quality monitoring

Mohamed Anis Fekih 1, 2 
2 AGORA - AlGorithmes et Optimisation pour Réseaux Autonomes
CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Lyon
Abstract : Mobile crowdsensing is an emerging and promising paradigm that has attracted much attention in recent years, especially for environmental monitoring. Coupled with the power of low-cost wireless sensor networks (WSN), it leverages population density to collect extensive data in many applications, such as air pollution and urban heat islands (UHI) monitoring. In fact, air pollution and UHI are one of the main problems that still suffer from a lack of characterization due to the limitations of traditional assessment methods employed in terms of cost, network size, and flexibility. Mobile crowdsensing and WSN aim at filling this gap by enabling large-scale deployments to improve the local knowledge of these phenomena on the one hand, while simultaneously involving the citizens in the process on the other hand. In this thesis, we mainly consider the air quality monitoring application with a mobile crowdsensing approach, while focusing on three main parts: 1) the design of low-cost participatory air quality monitoring systems; 2) the analysis of dense data from low-cost WSNs and their contribution to the fine-grained mapping of air quality; 3) the selection of the participants’ paths in order to improve the knowledge of the phenomenon while taking into account the constraints of travel distance and sensor errors. Through this work, we aim to show the potential of using low-cost WSN coupled with participatory sensing for air quality monitoring. In this vein, we carry out substantial experimental work on the design of a participatory air quality monitoring system from scratch. We provide engineering guidelines regarding the design of low-cost participatory environmental monitoring platforms. Moreover, we conduct extensive validation tests to evaluate the performance of our sensor nodes. In addition, we perform analysis on our sensors’ data and propose a general framework that allows the comparison of different regression and data assimilation strategies, based on numerical simulations and an adequate estimation of simulation and sensing error covariances. We also explore the impact of the sensing rate on the energy consumption and the mapping error. Furthermore, we tackle the problem of route selection in participatory sensing and propose two new approaches that take into account the participants’ constraints and the characteristics of air quality monitoring using low-cost WSN.
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Submitted on : Wednesday, June 29, 2022 - 6:40:37 PM
Last modification on : Tuesday, July 5, 2022 - 3:53:37 AM

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Mohamed Anis Fekih. Low-cost wireless sensor networks in participatory air quality monitoring. Other [cs.OH]. Université de Lyon, 2022. English. ⟨NNT : 2022LYSEI007⟩. ⟨tel-03709315⟩

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