Air Quality Index And Environment Monitoring
Air pollution remains a pressing global issue, necessitating efficient and scalable monitoring solutions beyond traditional sensor-based systems. This paper introduces a novel method for Air Quality Index (AQI) assessment by leveraging image-based analysis with MobileNetV2, a lightweight convolutional neural network (CNN). The approach utilizes environmental images—such as sky photographs—sourced alongside numerical AQI data from publicly available datasets on Kaggle, including the
Authors
- Sourjadip Pramanik (ORCID: https://orcid.org/0009-0009-5969-8873)
- G. Hemanth Kumar
- U. M.
- Sharon Shaijan
Publication Details
- Journal
- INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
- Published
- 2025-01-01
- DOI
- https://doi.org/10.56975/ijedr.v13i2.301227
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.00