MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202641073348 A) filed by Dr. Arun Ananthanarayanan; Dr. Prabhakar M.; Dr. Sathishkumar Hari; Dr. Ramesh Amugothu; Mrs. V. Suneetha; Mrs. Shwetha K; Dr. Vanajaroselin Chirchi; Dayananda Sagar Academy Of Technology And Management Dsatm; Ms. Aditi Purohit; and Mahesh Kumar A S on June 12, 2026, for Intelligent Ai-Driven Wireless Sensor Network System For Real-Time Health Monitoring, Predictive Diagnostics, And Remote Medical Communication.
Inventors include Dr. Arun Ananthanarayanan; Dr. Prabhakar M.; Dr. Sathishkumar Hari; Dr. Ramesh Amugothu; Mrs. V. Suneetha; Mrs. Shwetha K; Dr. Vanajaroselin Chirchi; Ms. Aditi Purohit; and Mahesh Kumar A S.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: [070] The present invention discloses an intelligent AI-driven wireless communication health monitoring sensor system for real-time physiological monitoring, predictive diagnostics, and remote healthcare management. The system comprises a plurality of wearable, implantable, portable, or ambient physiological sensors configured to continuously collect health-related parameters including heart rate, blood pressure, blood oxygen saturation, respiratory rate, body temperature, electrocardiogram signals, glucose levels, activity metrics, and other biological indicators. The collected data are transmitted through an adaptive wireless communication framework utilizing communication technologies such as Bluetooth Low Energy, Wi-Fi, ZigBee, LoRaWAN, cellular networks, and satellite communication systems. An edge intelligence processing unit performs signal conditioning, feature extraction, anomaly pre-screening, and communication optimization prior to forwarding the processed information to a cloud healthcare platform. An artificial intelligence analytics engine employing machine learning, deep learning, predictive analytics, and pattern recognition algorithms evaluates physiological information to detect abnormalities, generate personalized health assessments, estimate disease progression risks, and predict potential medical emergencies. The system further includes an automated emergency response framework configured to initiate real-time alerts to healthcare providers, caregivers, hospitals, and emergency services upon identification of critical health events. A security management layer incorporating encryption, authentication, blockchain-assisted integrity verification, and privacy-preserving learning mechanisms ensures secure handling of healthcare information. The invention additionally provides adaptive energy optimization, interoperability with healthcare information systems, and continuous learning capabilities to support proactive, personalized, secure, and scalable healthcare monitoring across hospitals, homes, telemedicine environments, and remote healthcare infrastructures. Accompanied Drawing [FIGS. 1-2]
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