Design of Smart IoT Device for Monitoring Short-term Exposure to Air Pollution Peaks

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dc.contributor.author Nizeyimana, Eric
dc.contributor.author Nsenga, Jimmy
dc.contributor.author Shibasaki, Ryosuke
dc.contributor.author Hanyurwimfura, Damien
dc.contributor.author Hwang, JunSeok
dc.date.accessioned 2022-05-16T11:05:40Z
dc.date.available 2022-05-16T11:05:40Z
dc.date.issued 2022-01
dc.identifier.uri https://repository.rsif-paset.org/xmlui/handle/123456789/159
dc.description Journal Article en_US
dc.description.abstract Air pollution spikes have been causing harm to human beings and the environment. Most exposure to Air pollution spikes has demonstrated a significant impact on mental health, especially children at an early age. That lead to suicide or depression. Previous research concentrated on air pollution in general. Existing monitoring systems do not consider Short-term air pollution peaks. This paper presents the co-design of the hardware and software for IoT to monitor air pollution spikes for a short duration in real-time monitoring. The system comprises two technologies like edge computing to capture short-term exposure and a mathematical model for distribution in analyzing the captured data. This system ensures the presence of the spikes start and end for each pollutant. Monte Carlo simulation has been used in this research to predict the next spike of each pollutant. Artificial Intelligent is used to analyze immutable data for a short term prediction. After the analysis, legislators based on intelligent contracts created using blockchain to reduce pollution based on its source. en_US
dc.publisher International Journal of Advanced Computer Science and Applications(IJACSA) en_US
dc.subject Short-duration air pollution peak/spike; real-time monitoring; short-term prediction; immutable data; blockchain; AI en_US
dc.title Design of Smart IoT Device for Monitoring Short-term Exposure to Air Pollution Peaks en_US
dc.type Article en_US

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