Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14928
Title: Air Quality Predictor to Reduce Health Risks and Global Warming
Authors: Dhanalakshmi, M
Vyshali Rao, K P
Bhuvaneshwari
Geetha Rani, E
Keywords: Booster
Enhanced Term Memory (Etm)
Internet Of Things (Iot)
Issue Date: 2023
Publisher: 2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings
Institute of Electrical and Electronics Engineers Inc.
Citation: pp. 1104-1109
Abstract: The increase in the pollution of air has led to the generation of many health risks. In the present-day much study has been going on to analyse the standard of air circulated in atmosphere has incited. The Inter-networking of Things (IoT) is been used vastly in various domains to boost the standard of the life of people. This paper describes the Internet of Things (IoT) integrated with low-cost sensor networking for monitoring the quality of air. The sensor networks helps in accumulating the values of each component of air. Considering the diffculty of air quality prediction, an ETM model has been proposed. Firstly, a single factor ETM model is designed which obtain the prediction value of each air component. Then, an ETM model with multifactor is designed. The ETM model considers important factors like data on the surrounding environment and weather data. The integrating booster integrates the two models. The results are obtained by assembling the prediction from the sub-nodes. © 2023 IEEE.
URI: https://doi.org/10.1109/ICACRS58579.2023.10404747
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14928
ISBN: 9.79835E+12
Appears in Collections:Conference Papers

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