MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202621057693 A) filed by Dr. Sumit Vashishtha; Kashish Kharate; Krity Kumari; Harshal Thakre; Himanshu Giri; Karan; Kunal Jamne; Nikhil Patel; Punit Punde; and Raj Kushwaha on May 06, 2026, for Agentic Ai-Based Device For Secure Patient Data Monitoring And Real-Time Cyber Threat Detection In Healthcare Systems.
Inventors include Dr. Sumit Vashishtha; Kashish Kharate; Krity Kumari; Harshal Thakre; Himanshu Giri; Karan; Kunal Jamne; Nikhil Patel; Punit Punde; and Raj Kushwaha.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: ABSTRACT Agentic AI-Based Device for Secure Patient Data Monitoring and Real-Time Cyber Threat Detection in Healthcare Systems The present disclosure relates to an Agentic AI-based device for secure patient data monitoring and real-time cyber threat detection in healthcare systems. The proposed invention integrates healthcare monitoring technologies, artificial intelligence, cybersecurity frameworks, and autonomous intelligent agents into a unified intelligent healthcare protection platform. The device continuously acquires physiological parameters including electrocardiogram signals, heart rate, blood pressure, oxygen saturation, respiration rate, glucose level, and body temperature through wearable sensors, smart medical devices, and Internet of Medical Things infrastructures. The collected healthcare data is processed using advanced Agentic Artificial Intelligence models capable of autonomous reasoning, adaptive learning, anomaly prediction, contextual healthcare analysis, and real-time decision-making for improving patient monitoring accuracy and emergency healthcare response. The disclosed invention further incorporates an intelligent cybersecurity monitoring engine configured to supervise healthcare communication networks, cloud interactions, authentication records, server access logs, and device communication patterns for identifying potential cyber threats targeting healthcare infrastructures. The cybersecurity engine utilizes machine learning and deep learning algorithms including convolutional neural networks, long short-term memory networks, reinforcement learning frameworks, and anomaly detection models to detect malicious activities such as ransomware attacks, malware propagation, phishing attempts, unauthorized access, packet spoofing, distributed denial-of-service attacks, and abnormal communication behavior. The Agentic AI system autonomously classifies threat severity levels and dynamically performs intelligent mitigation operations including compromised device isolation, firewall activation, encrypted communication enforcement, access restriction, cloud backup generation, and emergency alert transmission to healthcare administrators and medical personnel. The invention further provides secure cloud-based healthcare integration through encrypted communication protocols, blockchain-assisted verification mechanisms, multi-factor authentication systems, and zero-trust network architecture for protecting sensitive patient information during storage and transmission. The autonomous healthcare security framework ensures uninterrupted healthcare operations, secure remote patient monitoring, real-time healthcare analytics, and adaptive cyber defense capabilities across hospitals, telemedicine systems, smart healthcare centers, intensive care units, and Internet of Medical Things environments.
Disclaimer: Curated by HT Syndication.
