Smart City Gnosys

Smart city article details

Title	Predicting Air Pollution: A Smart Step In Pollution Management
ID_Doc	42671
Authors	Rastogi M.; Goel N.; Bansal M.
Year	2024
Published	Lecture Notes in Mechanical Engineering, 162
DOI	http://dx.doi.org/10.1007/978-981-97-1306-6_2
Abstract	The advancements in technology have introduced us to concepts like smart cities, smart devices, etc. A city can be considered as smart if it is liveable, inclusive, and sustainable. Other factors like building bold, strategic view for development, inclusive and accessible urban spaces, and services, having trust in government, proper waste management, and pollution management are some of the key factors which contribute significantly to making the city smart. Without oxygen, it is impossible to comprehend how humanity would survive. Modern human culture has had constant growth that has had a negative impact on the quality of the air. Daily transportation and home operations churn up dangerous pollutants in our surroundings. In the modern day, air quality monitoring and forecasting have become cumbersome tasks, particularly in developing nations like India. Managing pollution is becoming the need of the hour. This paper showcases how pollution management can be carried out with the help of machine learning techniques. A random forest algorithm has been applied to the sample data for predicting air pollution. It can be said that if air pollution is predicted at an earlier stage, it can contribute significantly to making the city smart. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Author Keywords	Air quality index; Air quality monitoring; Machine learning; Random forest

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