Intellectual Property India Publishes Patent Application for An Intelligent Iot Framework For Real-Time Air Quality Monitoring Using Machine Learning

MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641095137 A) filed by Dr. V. Balaji Vijayan; Dr. Venkatesan C; Dr. R. Dinesh; Dr. Sharavana K; and Madhusudhana V on August 06, 2026, for An Intelligent Iot Framework For Real-Time Air Quality Monitoring Using Machine Learning.

Inventors include Dr. V. Balaji Vijayan; Dr. Venkatesan C; Dr. R. Dinesh; Dr. Sharavana K; and Madhusudhana V.

The application for the patent was published on September 11, 2026, under issue no. 37/2026.

Abstract: Abstract: IoT sensors have the power to significantly improve the expertise of air quality and support efforts to minimize pollution. Researchers can identify and reduce possible health concerns brought on by air pollution with the aid of real-time IoT applications that monitor air quality systems. These applications also give useful data for research and policy-making. Machine learning algorithms can be employed by real-time IoT sensors to identify changes in air quality and notify them of potential health concerns. This makes it possible for us to effectively respond and take preventative action to safeguard our health and the environment.Because if we take preventative action to safeguard both personal health and the environment, these algorithms can notify us of possible health hazards. The IoT sensors aid in preventing respiratory and cardiovascular ailments, which can result in considerable healthcare expense benefits, by lowering the amounts of dangerous airborne pollutants. This information can be utilized to pinpoint potential problem areas for poor air quality and to provide remedies that can assist. Real-time data from IoT sensors can be used to make decisions regarding the quality of the air and human health by measuring air contaminants and their concentrations.Machine learning methods may be used to leverage IoT devices to identify changes in air pollution. Keywords: lot Sensors, Air Pollution, Machine Learning, Air Contaminants, Health HazardsA

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