Intellectual Property India Publishes Patent Application for 'AI-Based Image Classification System For Detecting Hazardous And Unsafe Living Conditions In Urban Environments' Filed by Dr. Pritibha Sukhroop; Ms. Karamjit Kaur; Mr. Neeraj Bohat; Ms. Isha; Dr. Ranjana Kumari; Dr. Ruchi Agarwal; Dr. Vijit Srivastava; and Mr. Bakshish Singh

MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202511126484 A) filed by Dr. Pritibha Sukhroop; Ms. Karamjit Kaur; Mr. Neeraj Bohat; Ms. Isha; Dr. Ranjana Kumari; Dr. Ruchi Agarwal; Dr. Vijit Srivastava; and Mr. Bakshish Singh, Meerut, Uttar Pradesh, on Dec. 13, 2025, for 'ai-based image classification system for detecting hazardous and unsafe living conditions in urban environments.'

Inventor(s) include Dr. Pritibha Sukhroop; Ms. Karamjit Kaur; Mr. Neeraj Bohat; Ms. Isha; Dr. Ranjana Kumari; Dr. Ruchi Agarwal; Dr. Vijit Srivastava; and Mr. Bakshish Singh.

The application for the patent was published on Jan. 23, under issue no. 04/2026.

According to the abstract released by the Intellectual Property India: "The present invention relates to an intelligent AI-based image classification system designed to automatically detect unsafe or hazardous living conditions in urban environments. The system utilizes a hybrid deep-learning architecture combining convolutional neural networks and transformer-based attention mechanisms to identify a wide range of hazards, including structural deterioration, electrical risks, sanitation issues, environmental threats, and unsafe occupancy patterns. Visual data collected from CCTV cameras, drones, mobile devices, and IoT-enabled sensors undergoes advanced preprocessing, semantic segmentation, and contextual metadata fusion to enhance detection accuracy. A multi-tier hazard classification and severity scoring framework evaluates the urgency and potential impact of each identified hazard, enabling timely prioritization by municipal authorities. The invention also features an adaptive edge-cloud deployment mechanism for real-time processing and a comprehensive decision-support dashboard for visualizing hazard maps, trends, and predictive analytics. By transforming raw imagery into actionable insights, the system improves urban safety, supports data-driven governance, and enables proactive risk mitigation in rapidly growing cities."

Disclaimer: Curated by HT Syndication.