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An Intelligent Air Quality Monitoring and Prediction System for Smart Cities

<!--HTML-->In 2019 99% of people were found to breathe air that exceeds WHO air quality limits, and 7 million people die from air pollution annually. This motivated the formation of the South African Consortium of Air Quality Monitoring. The international consortium was founded with the goal...

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Detalles Bibliográficos
Autor principal: Mckenzie, Ryan Peter
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:http://cds.cern.ch/record/2826384
Descripción
Sumario:<!--HTML-->In 2019 99% of people were found to breathe air that exceeds WHO air quality limits, and 7 million people die from air pollution annually. This motivated the formation of the South African Consortium of Air Quality Monitoring. The international consortium was founded with the goal of bringing together government institutions, HEP research institutions, and private enterprises into a mutually beneficial ecosystem to deliver an industry-disrupting open-source low-cost intelligent Internet-of-Things (IoT) air quality monitoring and prediction system for the benefit of the world. The system combines existing air quality sensors with a low-cost IoT network architecture to enable the use of Artificial Intelligence (AI) for air quality predictions. The expertise has been developed through the maintenance, operations, and Phase-II upgrade of the electronics of the ATLAS Hadronic Calorimeter as well as the use of machine learning techniques during data analysis of ATLAS data.