Landslide Monitoring & Early monitoring system
Traditional inspection couldn't catch early signs of slope failure in Kolhapur's landslide-prone hills. IoT geotechnical sensors plus AI analytics now continuously track slope stability and auto-alert authorities.
Problem Statement
Because of heavy rainfall, soil saturation, slope instability, and geological factors, the hilly areas of Jyotiba and Panhala in Kolhapur district are susceptible to landslides during the monsoon season. It is challenging to identify early indicators of slope failure using traditional monitoring techniques since they depend on routine inspections and human observations. Residents, visitors, public infrastructure, transit routes, and emergency personnel are all at greater risk as a result.
Solution
Velodynamics created an AI-powered Landslide Monitoring & Early Warning System that uses IoT-enabled geotechnical sensors, Automatic Weather Stations (AWS), AI-based analytics, and GIS visualization to continuously monitor slope stability. The system anticipates possible slope failures, finds early signs of landslide activity, and automatically notifies authorities so that prompt preventive action can be taken.
Pilot Deployment: Kolhapur's Jyotiba Hills and Panhala Fort Region
Functionalities
Slope Dynamics & Displacement Tracking
Monitor real-time slope movement and ground displacement to detect structural instabilities as they occur.
AI Predictive Threat Intelligence
Leverage AI algorithms for early landslide prediction, risk assessment, and historical trend analysis.
Multi-Sensor Data Integration
Connect GNSS/GPS, inclinometers, piezometers, and crack sensors into a unified monitoring network.
Soil moisture monitoring at multiple depths
Meteorological Risk Analytics
Integrate weather station data and rainfall threshold analysis to evaluate precipitation-driven slope failure risks.
Ground displacement monitoring
Subsurface & Hydrological Sensing
Track pore water pressure and multi-depth soil moisture to measure internal saturation levels.
Weather station integration
GIS & AI Visual Surveillance
Combine GIS-based hazard mapping with AI-enabled cameras for precise spatial and visual site monitoring.
AI-enabled visual surveillance cameras
Tech Stack
Layer
Technology Stack
Frontend/Mobile
React
Backend
Python
Database
MSSQL
Cloud & Hosting
AWS
Notifications & Services
Firebase Cloud Messaging (Mobile Application) / MessageHUB / SignalR
Impact on Client
24×7 Real-Time Monitoring: Continuous surveillance of slope movement, rainfall, soil moisture, ground displacement, and pore water pressure.
Early Warning Capability: AI-based predictions provide advance alerts before potential slope failures, enabling timely preventive measures.
Faster Emergency Response: Automated alerts allow disaster management teams to mobilize resources and respond quickly.
Improved Decision-Making: Centralized dashboards provide live data, risk levels, and actionable insights for authorities.
Enhanced Public Safety: Supports timely evacuation of residents, pilgrims, tourists, and commuters from high-risk zones.
Inter-Departmental Coordination: Enables seamless collaboration between the District Disaster Management Authority (DDMA), Public Works Department (PWD), Revenue Department, Forest Department, Police, and Emergency Services.
Reduced Manual Inspections: Remote IoT-based monitoring minimizes the need for frequent field visits while improving monitoring accuracy.
Protection of Critical Infrastructure: Helps safeguard roads, hill routes, public utilities, heritage sites, and essential infrastructure from landslide damage.
Testimonials
The Landslide Monitoring & Early Warning System has provided us with real-time visibility into slope conditions at Jyotiba and Panhala. The AI-driven alerts and continuous monitoring significantly enhance our ability to take preventive action and improve public safety during the monsoon season.”
Prasad Sankpal
District Disaster Management Officer
ZP
July 2024
