How AI-based system is expected to make AQI forecast sharper in Delhi
GS3Economy · S&T · Environment · Security· IT, AI, semiconductors & computing· Prelims + Mains·
Why in news
IIT-Kanpur’s Airawat Research Foundation (ARF) is partnering with the Delhi Environment department to develop an AI-based system for sharper Air Quality Index (AQI) forecasting.
Background
The project aims to improve prediction accuracy and response times for Delhi's winter pollution by using machine learning to analyze live data. It addresses limitations of current models, such as outdated emission databases and lack of year-round testing, while integrating with the Graded Response Action Plan (GRAP) and National Clean Air Programme (NCAP).
Facts for Prelims
- S&TMachine learning models are being used to provide granular, real-time AQI forecasts in Delhi.
- BodyAirawat Research Foundation (ARF) is a research body associated with IIT-Kanpur.
- SchemeNCAP (National Clean Air Programme) is the central initiative for air quality management in India.
- SchemeGRAP (Graded Response Action Plan) is a set of emergency measures to control air pollution in Delhi-NCR.
For Mains
Q. Discuss how the integration of Artificial Intelligence and machine learning can enhance the efficacy of India's National Clean Air Programme (NCAP) in urban centers.
Dimensions to cover in your answer
- Data granularity: Transitioning from regional averages to hyper-local, street-level pollution forecasting using AI.
- Predictive governance: Shifting from reactive measures to proactive emergency responses via early warning systems.
- Database modernization: Addressing the lag in emission inventories to improve the accuracy of machine learning inputs.
Keywords: Predictive Analytics · Hyper-local Monitoring · Data-driven Governance · Environmental Informatics · Machine Learning
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This note is generated automatically from SatyaDheesh's news feed and mapped to the UPSC CSE syllabus. Check facts against the original report or PIB before using them in an answer.