This project demonstrates a health monitoring system for waterborne diseases in rural communities, implying improved responses to public health crises.
The Northeast Indin rural districts lack sanitation facilities, timely health updates, and health response delays, which, compounded, drive the cyclical incidence of waterborne illnesses in these regions. To address these challenges, the proposed project, which involves the use of Smart Community Health Monitoring, aims to advance the detection, forecasting, and response to cholera, typhoid, and diarrheal diseases. By imitating the IoT-enabled health monitoring system of water quality sensors, mHealth reporting, and the health risk machine learning algorithm, we plan to monitor the disease/mater health risk factors and the disease/mater health analytics in real time. Community water sources access, illness reporting, and community water sources health monitoring unattended wards collection allow timely alerts for community health workers and community members. With early, actionable insight, the aimed rural community system will provide opportunistic infection control. In relation to the described partnerships, the proposed system will focus government efforts to infection control and system interruption alleviate infection control and system interruption to infection control. Public health exclusion, adopted technology, system participation, and system uninterrupted community focus coordinated system increase to supported the proposed community resilient system strengthen system to proposed community supported system to increase risk resilient to proposed community supported to increase system increased resilient system to proposed community supported to increase risk resilient to proposed community supported.
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N et al. (2026) studied this question.
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