Engineering and Technology
OPEN ACCESS
AI-Driven Pollution Monitoring and Mitigation Framework for Delhi: Integrating Drones, IoT, and Predictive Analytics for Sustainable Air Quality Management
DOI
Crossref DOI
10.37547/tajet/v7i11-309
tajet
2025
VOL. 7
/ NO. 11
NOVEMBER
RESEARCH OVERVIEW
Abstract
This paper presents an AI-driven framework for real-time monitoring, prediction, and mitigation of urban air pollution in Delhi, India. The proposed system integrates drone-based air quality sensing, IoT-enabled data collection, and AI predictive analytics to forecast pollution levels and recommend proactive interventions. By combining drone data, IoT sensors, and meteorological information, deep learning models forecast pollution spikes and optimize mitigation measures. The system offers a scalable, replicable model for proactive pollution management across global cities.
RESEARCH TOPICS
Keywords
Air Pollution
Artificial Intelligence
IoT
Drones
Predictive Analytics
Smart Cities
Deep Learning
Meteorological
Environmental Technology
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SOURCES & SCHOLARSHIP
References
- IEEE, 'AI for Environmental Sustainability: Emerging Technologies,' IEEE Spectrum, 2024.
- Government of India, 'National Clean Air Programme (NCAP),' Ministry of Environment and Forests, 2022.
- S. Gupta et al., 'Drone-Based Air Quality Monitoring Systems,' Journal of Smart Systems, vol. 15, no. 4, 2023.
- P. Sharma and R. Singh, 'IoT and Machine Learning for Air Quality Prediction,' IEEE Trans. on Environmental Eng., 2023.
- A. Kumar et al., 'AI-Enabled Urban Pollution Management Frameworks,' Int. Journal of Smart Cities, 2024