MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202611096004 A) filed by Dr. Ashish Nagila; Dr. Taru Tevatia; Kalyan Savalapurapu; Avani Anawardekar; A. Deepika; Alekhya Thirumalasetty; G Madhusudan; Kadiyala Jhansi Rani; Ms. S. Revathi; Dr. N. Mohananthini; Adnan Mohammed Iqbal Shaikh; and Mohd Arif Abdul Farid Shaikh on August 08, 2026, for Machine Learning And 6g-Enabled Iot System For Real-Time Pollution Monitoring And Adaptive Control In Smart Cities.
Inventors include Dr. Ashish Nagila; Dr. Taru Tevatia; Kalyan Savalapurapu; Avani Anawardekar; A. Deepika; Alekhya Thirumalasetty; G Madhusudan; Kadiyala Jhansi Rani; Ms. S. Revathi; Dr. N. Mohananthini; Adnan Mohammed Iqbal Shaikh; and Mohd Arif Abdul Farid Shaikh.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: Environmental pollution has become one of the major challenges faced by modern cities due to rapid urban growth, industrial expansion, increasing traffic, and rising energy consumption. Over the years, several environmental monitoring systems have been introduced to measure air quality, water quality, environmental noise, weather conditions, and industrial emissions. While these systems have improved the availability of environmental data, most of them primarily focus on collecting and displaying sensor readings. Many existing solutions depend on isolated monitoring stations, periodic inspections, or threshold-based alerts, making it difficult to recognize changing pollution patterns in time. In addition, environmental information is often analyzed separately without effectively combining multiple pollution sources, historical observations, traffic conditions, and weather variations into a single decision-making process. This may delay pollution control measures and reduce the ability of authorities to respond proactively. The present invention provides a Machine Learning and 6G-Enabled IoT System for Real-Time Pollution Monitoring and Adaptive Control in Smart Cities, which brings together distributed IoT sensing devices, high-speed 6G communication, intelligent feature engineering, machine learning-based prediction, cloud-enabled monitoring, and adaptive environmental management within one integrated framework. The invention generates meaningful environmental indicators including the Air Pollution Severity Index (APSI), Water Quality Degradation Score (WQDS), Environmental Risk Level (ERL), Urban Emission Density Index (UEDI), and Adaptive Pollution Control Score (APCS) to represent overall environmental conditions in a structured manner. These indicators are analyzed to identify pollution trends, predict future environmental risks, detect pollution hotspots, and recommend suitable pollution control measures. The framework continuously learns from newly collected environmental observations and operational feedback, allowing recommendations to improve over time. The proposed invention supports faster environmental decision-making, improves pollution prediction accuracy, strengthens resource planning, enables timely pollution mitigation, enhances public health protection, and provides a scalable and intelligent environmental management solution for future smart city ecosystems. FIG.1
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