MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641009233 A) filed by Dr. R. Thenmozhi; Dr. Praveengugulothu; Drrathina Kumar; Mrs. Uma S; Mrs. Anushree R; Mrs. Sowmya B J; Dr. Iffath Fawad; and Ms. Jeyakani. P, Chennai, Tamil Nadu, on Jan. 29, for 'ai-based predictive system for early diagnosis of chronic diseases using multimodal medical imaging.'

Inventor(s) include Dr. R. Thenmozhi; Dr. Praveengugulothu; Drrathina Kumar; Mrs. Uma S; Mrs. Anushree R; Mrs. Sowmya B J; Dr. Iffath Fawad; and Ms. Jeyakani. P.

The application for the patent was published on Feb. 13, under issue no. 07/2026.

According to the abstract released by the Intellectual Property India: "AI-Based Predictive System for Early Diagnosis of Chronic Diseases Using Multimodal Medical Imaging AI-powered system for real-time human abnormal event detection in public spaces, designed to enhance safety and security by leveraging artificial intelligence (AI), machine learning (ML), computer vision, and sensor integration. The system continuously monitors human activity in public environments through a network of surveillance cameras and various sensors (thermal, motion, environmental, etc.). It processes the data in real-time, using AI algorithms to detect and analyze abnormal human behaviors or events, such as violent actions, medical emergencies, suspicious activities, crowd disturbances, or environmental hazards. Once an abnormal event is detected, the system triggers real-time alerts to security personnel or emergency responders, enabling rapid intervention. The AI engine employs machine learning models to learn from the data over time, improving its ability to identify potential threats and reduce false alarms. Additionally, the system's integration of cloud and edge computing ensures fast data processing and scalable deployment across a variety of public spaces, including airports, transportation hubs, commercial buildings, and large events. The invention emphasizes privacy protection by focusing on behavior rather than personal identification, complying with privacy regulations such as GDPR. This system provides an innovative, automated solution for enhancing public safety, enabling more efficient monitoring and intervention in dynamic, high-traffic environments."

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