MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641100702 A) filed by Jeppiaar Institute Of Technology on August 20, 2026, for Smart Community Health Monitoring System For Waterborne Disease Prevention Using Iot And Machine Lea.
Inventors include R. Ruth Shobitha; S. Kedarnath Sai Singh; S. Hariharan; K. A. Anand; and A. Gokul Prasanth.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: ABSTRACT OF THE INVENTION (to be given along with complete specification on separate page) Waterborne diseases such as cholera, typhoid, dysentery and diarrhoeal infections remain a major public health concern in communities that depend on untreated or partially treated water sources, particularly in rural and semi- urban regions lacking real-time water testing infrastructure. Conventional water quality assessment relies on manual sample collection and laboratory analysis, a process that is time-consuming and labour-intensive, and often confirms contamination only after community exposure has already occurred. This patent discloses a Smart Community Health Monitoring System for the early prediction and prevention of waterborne diseases through continuous, automated monitoring of water quality. The system employs pH, turbidity, total dissolved solids (TDS) and temperature sensors interfaced with a microcontroller unit to continuously acquire water quality data from community water sources. The acquired data is transmitted to a cloud platform where a trained machine learning model analyses the parameter patterns to classify the water source as safe or at risk, and to predict the likelihood of a waterborne disease outbreak. When the predicted risk exceeds a predefined threshold, the system automatically triggers real-time SMS and cloud-based alerts to local health authorities and community members, enabling prompt corrective action. This patent thus provides a low-cost, scalable and proactive alternative to conventional manual water testing, reducing detection latency and enabling community-level outbreak prevention.
Disclaimer: Curated by HT Syndication.
