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A Survey Paper on Smart Community Health Monitoring: AI-Driven Early Warning Systems for Water-Borne Diseases in Rural Northeast India

M Amruth Aiyappa, Naomi Ria D’Souza

Abstract


Water-borne diseases are a serious concern for rural communities in Northeast India, where the lack of healthcare facilities and tough terrain make it hard to get timely help. Luckily, recent advancements in smart health monitoring systems that leverage AI, IoT, and data analytics are opening up exciting new ways to spot and prevent disease outbreaks before they escalate. This survey takes a closer look at the current state of community-based health monitoring and early warning systems aimed at tackling water-borne illnesses. It dives into existing frameworks, sensor technologies, AI-driven analytics, and deployment strategies specifically designed for rural settings. We also discuss key challenges such as data quality, system scalability, community involvement, and how these systems can integrate with local healthcare. Alongside these challenges, we highlight current solutions and future possibilities. This paper seeks to offer a thorough review for researchers, policymakers, and practitioners who are working to establish effective early warning systems for water-borne diseases in resource-constrained rural areas.


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References


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