The air pollution, with its impacts on human health and the environment, is a growing global issue. In this article, we propose the implementation of a Multi-Interface Mobile Gateway (MIMG) with LPWAN technology(1) in public transportation vehicles for monitoring air quality. The idea is to use a mobile monitoring system that can reduce the cost of the classical fixed air pollution and environmental monitoring stations. This approach addresses challenges such as data transfer, interference, and data pre-processing to reduce the amount of data sent over the remote data management center. We conducted a system emulation to evaluate some data forwarding strategies and to evaluate the overall traffic load generated by the mobile station over the overall network. Furthermore, the MIMG manages the use of the communication interface, uses data aggregation techniques to reduce the amount of data to be transmitted, and utilizes machine learning to enhance the accuracy of the low-cost sensor readings. Our approach has significant applications in urban air quality management.

Multi-interface mobile gateways for LPWAN-based air pollution monitoring

Dutta A.;Tropea M.;De Rango F.
2024-01-01

Abstract

The air pollution, with its impacts on human health and the environment, is a growing global issue. In this article, we propose the implementation of a Multi-Interface Mobile Gateway (MIMG) with LPWAN technology(1) in public transportation vehicles for monitoring air quality. The idea is to use a mobile monitoring system that can reduce the cost of the classical fixed air pollution and environmental monitoring stations. This approach addresses challenges such as data transfer, interference, and data pre-processing to reduce the amount of data sent over the remote data management center. We conducted a system emulation to evaluate some data forwarding strategies and to evaluate the overall traffic load generated by the mobile station over the overall network. Furthermore, the MIMG manages the use of the communication interface, uses data aggregation techniques to reduce the amount of data to be transmitted, and utilizes machine learning to enhance the accuracy of the low-cost sensor readings. Our approach has significant applications in urban air quality management.
2024
VANET
Public Transportation
Air Quality Monitor
Multi-Interface Mobile Gateway
LPWAN
MQTT
CoAP
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/399625
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