Air Quality Prediction and Purifier Recommendation With E-commerce Integration
- DOI
- 10.2991/978-94-6463-471-6_11How to use a DOI?
- Keywords
- Air quality prediction; Amazon product API; Real-time AQI measurement report; sustainable solution; environment; smart architecture
- Abstract
This paper amalgamates air quality prediction, purifier recommendation, and e-commerce into a streamlined platform. Leveraging Streamlit and React, it offers real-time Air Quality Index (AQI) detection based on location, aiding users in assessing breathing suitability. By employing Random Forest Regression, the system achieves an exceptional 99.7% accuracy, surpassing similar applications. The predictive model not only forecasts air quality but also recommends appropriate air purifiers, enhancing user well-being. Seamlessly integrating e-commerce functionalities, it allows direct access to recommended purifiers, facilitating swift and informed purchase decisions. This innovative solution not only delivers precise AQI insights but also ensures a user-friendly interface, empowering individuals to make informed choices for healthier living environments.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Aman Raj Sharma AU - Harshit Khare AU - Kaavya Kanagaraj PY - 2024 DA - 2024/07/30 TI - Air Quality Prediction and Purifier Recommendation With E-commerce Integration BT - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024) PB - Atlantis Press SP - 109 EP - 117 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-471-6_11 DO - 10.2991/978-94-6463-471-6_11 ID - Sharma2024 ER -