IIT Mandi develops AI-based real-time landslide early warning system
In a significant advancement for disaster management, scientists at the Indian Institute of Technology (IIT) Mandi have developed a real-time landslide monitoring and early warning system. This innovative system aims to reduce the loss of life and infrastructure damage in landslide-prone regions, particularly in the Himalayan area.
Collaboration and Development
The project was undertaken in collaboration with the National Mission on Himalayan Studies and various partner agencies. The system employs a network of sensors strategically installed at vulnerable sites to transmit real-time data, enabling the detection of ground movement as minute as less than one millimeter.
How the System Works
Once even the slightest ground movement is detected, the system is automatically activated. Various warning mechanisms are triggered in vulnerable zones, including:
- Hooters
- Blinkers
Simultaneously, alerts are sent to local authorities to facilitate a rapid response to potential landslide threats.
Expert Insights
Professor Varun Dutt from IIT Mandi elaborated on the system’s capabilities, stating, “If there is a movement of even less than one millimeter on a hill, the system gets activated. Once triggered, it sends alerts to ‘warning poles’ installed in vulnerable areas such as valleys or along roads below the hill. This activation sets off a hooter and blinker, alerting people about the possibility of a landslide.” Additionally, alerts are disseminated through SMS and a web application to the District Disaster Management Authority (DDMA) control room, from where the information is relayed to the police, the National Disaster Response Force (NDRF), and other relevant agencies.
Integration of Satellite Imagery
Beyond ground-based sensors, the system also integrates satellite imagery to monitor larger-scale terrain movement over time. This integration enhances the accuracy of risk assessments. Professor Dutt noted, “Our system works in real time, but satellite data provides information of a very high level, with a resolution of about 20 meters by 20 meters, while our system has millimeter-level resolution. While satellite data helps us understand whether there was any movement in a particular area over a period of 14 days to two months, our system can detect much finer changes.”
Future Enhancements
The Government of India has initiated the NISAR mission, which will gradually provide additional data that can be integrated into the warning system. As this satellite data becomes accessible, the accuracy and timeliness of the warnings generated will further improve. Currently, satellite data is received every two weeks, and researchers are working on integrating this data with their system to issue more precise alerts.
Deployment and Effectiveness
The technology has already been deployed at three landslide-prone locations in Mandi district, where it is providing continuous monitoring and early warning alerts. Researchers claim that the model, which utilizes machine learning and advanced analytics, has achieved over 90 percent accuracy in predicting landslides. This marks a significant step forward in disaster preparedness and mitigation in the Himalayan region.
Conclusion
The development of this AI-based real-time landslide early warning system by IIT Mandi represents a crucial advancement in safeguarding communities vulnerable to landslides. By combining ground sensors with satellite data, the system not only enhances immediate response capabilities but also contributes to long-term risk assessment and management strategies.
Note: The information presented in this article is based on the latest developments as of February 2026 and aims to highlight the importance of technological advancements in disaster management.
