Title:AI-Powered Smart Community Health Monitoring and Early Warning System for Waterborne Diseases


Authors: Prabhat Choudhary, Hritik Patel, Nandani Rathore, Vandana Kate, Priyanshi Patel, Nisha Rathi, Nivedika Gour


Published in: Volume 3 Issue 1 Jan June 2026, Page No.229-234


Keywords:Artificial Intelligence, Waterborne Diseases, Smart Health Monitoring, Early Warning System, IoT Sensors, Rural Health, Disease Prediction.


Abstract:Waterborne diseases like cholera, typhoid, and diarrhoea are a major threat to public health in India. This is especially true in rural areas, where real-time monitoring and early detection are often lacking. The United Nations reports that about 37.7 million people suffer from waterborne diseases each year. And diarrhoea causes 117,000 deaths among under-5 children, which is around 13% of the total deaths in this age group. This paper suggests an AI-powered Smart Community Health Monitoring and Early Warning System to overcome the delays in outbreak detection and the shortcomings of manual reporting. The system combines portable sensors that measure pH, turbidity, and conductivity integrated within a module making a handy device with health reports gathered through a multilingual mobile app. All data sync to a cloud platform, where an AI analytics engine examines environmental and clinical patterns to predict disease risks. When it detects high-risk conditions, the system sends alerts and safety guidance to health workers and people through notification; its multilingual feature makes it accessible for everyone. A feedback mechanism helps to improve prediction with ongoing use. This easy-to-use and scalable system gives communities proactive, affordable, and inclusive health information, enhancing public health response and preventing the spread of waterborne diseases in underserved areas.


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