Challenge Area:
Water quality monitoring in remote areas.

Problem Statement:
Lack of real-time water quality data in rural communities leads to health risks from contaminated water sources.

Solution Concept:
Deploy an IoT-AI system with sensors to monitor water quality parameters (e.g., pH, turbidity) and use machine learning to predict contamination risks, alerting communities via SMS.

Expected Impact:
Ensure safe water access for 20,000 people in 10 villages.

Next Steps:
Design low-cost sensors, develop predictive models, and partner with local governments for deployment.

Challenge Area:
Water Quality

Problem Statement:
Contaminated water sources in rural areas go undetected, causing health crises.

Solution Concept:
Build a water quality prediction system using IoT sensor data and random forest models to detect contaminants. The PoC includes robust data cleaning for sensor noise and scalable cloud-based processing.

Expected Impact:
Reduces waterborne illnesses by 40% in 10,000+ communities.

Next Steps:
Deploy low-cost sensors, integrate with local government systems, and add real-time alerts.