AiCareAir: Hybrid-Ensemble Internet-of-Things Sensing Unit Model for Air Pollutant Control-Reference-Cited by-同舟云学术

AiCareAir: Hybrid-Ensemble Internet-of-Things Sensing Unit Model for Air Pollutant Control

Published:2024-07-01 Issue:13 Volume:24 Page:21558-21565
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Borah Jintu¹^ORCID,Mohd. Nadzir Mohd. Shahrul²,Cayetano Mylene G.³^ORCID,Majumdar Shubhankar⁴^ORCID,Ghayvat Hemant⁵,Srivastava Gautam⁶^ORCID

Affiliation:

1. Department of ECE, National Institute of Technology at Meghalaya, Shillong, Meghalaya, India

2. Department of Environmental Sciences, UKM, Bangi, Selangor, Malaysia

3. Department of Earth Science and Meteorology, UP Diliman, Manila, Philippines

4. Department of Electronics and Communication, National Institute of Technology at Meghalaya, Shillong, India

5. Innovation Department, Technology University of Denmark, Copenhagen, Denmark

6. Department of Computer Science and Math, Lebanese American University, Beirut, Lebanon

Funder

Association of Southeast Asian Nations (ASEAN)-India Science and Technology Collaboration (AISTIC) Funding from the Department of Science and Technology, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10577556/10529960.pdf?arnumber=10529960

Reference35 articles.

1. A nonlinear regression model estimating single source concentrations of primary and secondarily formed PM2.5

2. Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

3. Neural network prediction model for fine particulate matter (PM2.5) on the US–Mexico border in El Paso (Texas) and Ciudad Juárez (Chihuahua)

4. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

5. An innovative hybrid air pollution early-warning system based on pollutants forecasting and Extenics evaluation

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