A national workshop in New Delhi on 27 November brought together researchers, officials, and industry groups to examine how AI and low-cost sensors can support cleaner air in Indian cities. The Airawat Research Foundation at IIT Kanpur hosted the meeting at the India International Centre.
The discussion took place during a period of severe air pollution across major urban centers. Speakers stressed that cities need dense and real-time data to guide health responses and local action. The workshop focused on ways to scale sensor networks, strengthen data systems, and move toward a common monitoring framework supported by AI and machine learning.
ARF CEO Amar Nath opened the meeting with a blueprint for Clean Air Delhi. He said, “India needs air-quality systems that are not just scientifically solid, but also scalable, affordable, and deployable in every city. AI-enabled LCS networks are central to that transformation.”
S. N. Tripathi, who leads the AI Centre for Sustainable Cities at IIT Kanpur, outlined work on sensor calibration and detailed pollution mapping. He said, “Low-cost sensors, when paired with rigorous analytics and transparent calibration, can unlock neighborhood-level air-quality insights that India has never had before.”
Tripathi also explained how cities can plan large sensor networks. His team uses genetic-algorithm models to guide placement across different budgets. He showed maps from Surat and Mumbai where these models helped identify priority locations. He said this approach helps cities stretch limited funds while still covering high-risk areas.
Industry participants described the rise of domestic sensor production. Namita Gupta of Airveda said India now has the capacity to build and distribute sensors at the scale cities demand. She pointed to the need for stronger data quality processes and more support for QA and QC facilities.
Vamsi Krishna of Aurassure joined the session to outline how private firms are working with city agencies to fill data gaps and support rapid deployment of monitoring devices.
CSIR-NPL Chief Scientist Govind Gupta explained how low-cost sensors expand non-regulatory monitoring. He said, “Low-cost sensors do not replace regulatory monitors, but they are essential for dense, real-time public exposure measurement and hyperlocal planning.” He noted that a new gas sensor calibration facility at CSIR-NPL is planned for 2026.
Researchers Sagnik Dey and Sofiya from IIT Delhi shared findings showing how dispersed sensor networks capture short-term spikes that fixed stations often miss. Their work links localized data with checks on recent traffic and industrial measures.
A co-creation session led by Davender Sethi and Ankita Dwivedi guided participants through draft frameworks for AI-led governance, data protocols, and sensor deployment standards.
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