Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Air pollution is a growing concern worldwide, affecting public health, the environment, and overall quality of life. Accurate prediction of air pollution levels can help individuals and authorities take preventive measures. This project aims to develop a web-based application that uses GPS to detect the user's current location, fetches real-time weather data, and allows users to select any location to predict future air pollution levels. By leveraging machine learning models, the system analyses historical weather and pollution data to forecast air quality, enabling users to make informed decisions.
Keywords:
Air Quality Index , Global Positioning System , Data Flow Diagram ,Unified Modeling Language , User Interfcae , Applications Programming Interface , China Air Quality Index , Long Short Term Memory
Cite Article:
"Advanced Air Pollution Prediction Using Geolocation And Machine Learning ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.d233-d237, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505332.pdf
Downloads:
000439
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator