MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202611073036 A) filed by Dr. Deepesh Bhardwaj; Ms. Lakshmi Sai Varshini Yedavalli; Dr. Puneet Sapra; Utkarsh Rastogi; Venkata Satya Praveen Rani; Dr S Kusuma; Nancy Sharma; Gowtham M; Suresh Dannana; N. Sasikala; S. Muthukumar; and Amar Pal Yadav on June 12, 2026, for Iot Integrated Real-Time Kidney Stone Monitoring And Detection System With Deep Learning Image Processing.
Inventors include Dr. Deepesh Bhardwaj; Ms. Lakshmi Sai Varshini Yedavalli; Dr. Puneet Sapra; Utkarsh Rastogi; Venkata Satya Praveen Rani; Dr S Kusuma; Nancy Sharma; Gowtham M; Suresh Dannana; N. Sasikala; S. Muthukumar; and Amar Pal Yadav.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: The present invention relates to the development of a system for continuous real-time monitoring and detecting kidney stones with deep learning-based image processing technologies. The system consists of a wearable physiological monitoring module, a smart urine analysis module, an image acquisition module, an IoT connection gateway, a cloud platform, a deep learning image processing engine, a predictive analytics engine, a digital kidney twin module, and a healthcare communication module. It collects physiological parameters, urine biomarkers, hydration levels, and imaging data, which are uploaded to the cloud. The deep learning engine enhances images and accurately segments kidneys, detects stones, and classifies sizes. The predictive analytics engine assesses risks for kidney stone recurrence and urinary obstruction using machine learning. The digital kidney twin module simulates kidney stone progression with personalized data. Mobile and physician applications provide alerts, hydration advice, diet recommendations, and remote patient monitoring. FIG.1
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