MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202621099848 A) filed by Dr. Piyush R. Telang; Mr. Kshitij S. Bairagi; and Prof. Dr. Nitin N. Mundhe on August 18, 2026, for A Multi-Sensor Based Air Quality Monitoring System For Geographic Pollution Assessment, Source Identification And Environmental Sustainability Management.
Inventors include Dr. Piyush R. Telang; Mr. Kshitij S. Bairagi; and Prof. Dr. Nitin N. Mundhe.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The present invention relates to a multi-sensor based air quality monitoring system for geographic pollution assessment, source identification and environmental sustainability management. The system comprises a plurality of geographically distributed environmental monitoring units configured to acquire particulate matter, gaseous pollutants, meteorological parameters and geographical information. Environmental observations are processed through an adaptive sensor confidence evaluation engine configured to dynamically determine reliability coefficients for individual sensing modules, followed by a multi-level sensor fusion engine configured to generate integrated environmental datasets. Processed information is transmitted to a centralized cloud platform comprising a geospatial analytics engine configured to generate dynamic environmental micro-zones, a pollution source attribution engine configured to identify probable emission sources, a pollution propagation prediction engine configured to estimate future pollutant movement, and an environmental sustainability index engine configured to evaluate environmental health by integrating pollution intensity, ecological resilience, vegetation characteristics, atmospheric stability and human exposure. A decision support engine generates environmental management recommendations including pollution mitigation strategies, environmental alerts, sustainability planning and resource prioritization. The invention further incorporates distributed edge processing, adaptive communication management and continuous machine learning to improve monitoring accuracy, predictive capability and environmental decision support. The proposed system provides an intelligent environmental monitoring framework capable of supporting smart cities, industrial environments, environmental regulatory authorities and sustainability management through real-time geospatial environmental intelligence. FIG. 1
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