IIT Mandi Develops Vision-Based Flood Warning Sensor for Early Alerts

A Step Forward in Preventing Flood Damage with Real-Time Monitoring Technology

IIT Mandi has made a significant advancement in flood management with the development of a Vision-Based Flood Warning Sensor designed to provide timely alerts about potential flood risks. This innovative prototype, created by students Om Maheshwari, Garvit, Varnika, Akshay, Karthik, and Harika, aims to enhance flood prediction systems and reduce the potential damage caused by rising water levels.

According to Om Maheshwari, the sensor incorporated into the prototype is designed to provide real-time data on the water level of rivers. The sensor will be strategically placed beneath bridges and will transmit critical data through satellite connections. By establishing a baseline of the river’s normal water level, the sensor can effectively monitor deviations caused by heavy rainfall, triggering early warnings when water levels rise to dangerous heights.

Unlike previous flood sensors that were positioned within the river and vulnerable to being washed away during floods, this new sensor is installed at a safe distance above the water level. It will transmit data reliably even during high-water events. To ensure comprehensive coverage, the sensors will be distributed across a 10-15 km radius, allowing for accurate monitoring of the river’s water levels over larger areas.

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This technology is particularly relevant for regions in Himachal Pradesh, where seasonal rains cause rivers and streams to swell, posing significant risks to nearby populations. Many communities in the state are located along the banks of these waterways, and flooding during the monsoon season can result in severe damage to both life and property. Recognizing this vulnerability, the students at IIT Mandi have developed this prototype to address the need for an early warning system that can aid in timely evacuations and reduce the impact of floods.

The project is currently in its prototype stage, and further testing and refinement will be necessary before it can be fully implemented. However, the initial development marks a promising step toward improving flood management and disaster preparedness in flood-prone regions.