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Smart Pollution Alert System Using Machine Learning

Smart Pollution Alert System Using Machine Learning

P. Chitra, S. Abirami
Copyright: © 2019 |Pages: 17
ISBN13: 9781522577904|ISBN10: 1522577904|ISBN13 Softcover: 9781522586210|EISBN13: 9781522577911
DOI: 10.4018/978-1-5225-7790-4.ch011
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MLA

Chitra, P., and S. Abirami. "Smart Pollution Alert System Using Machine Learning." Integrating the Internet of Things Into Software Engineering Practices, edited by D. Jeya Mala, IGI Global, 2019, pp. 219-235. https://doi.org/10.4018/978-1-5225-7790-4.ch011

APA

Chitra, P. & Abirami, S. (2019). Smart Pollution Alert System Using Machine Learning. In D. Mala (Ed.), Integrating the Internet of Things Into Software Engineering Practices (pp. 219-235). IGI Global. https://doi.org/10.4018/978-1-5225-7790-4.ch011

Chicago

Chitra, P., and S. Abirami. "Smart Pollution Alert System Using Machine Learning." In Integrating the Internet of Things Into Software Engineering Practices, edited by D. Jeya Mala, 219-235. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7790-4.ch011

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Abstract

This chapter proposes a novel mobile-based pollution alert system. The level of the pollutants is available in the air quality repository. This data is updated periodically by collecting the information from the sensors placed at the monitoring stations of different regions. A model using artificial neural network (ANN) is proposed to predict the AQI values based on the present and previous values of the pollutants. The ANN model processes the normalized data and predicts whether the region is hazardous or not. A novel mobile application which could be used by the user to know about the present and future pollution level could be developed using a progressive web application development environment. This mobile application uses the location information of the user and helps the user to predict the hazardous level of the pollutants in that particular location.

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