AIML-Powered Railway Animal Detection & Alert System
Rail Kavach is a smart railway safety system designed to prevent animal accidents on railway tracks using AI-powered detection, automated alerts, and proactive train control measures. The system ensures real-time monitoring, alerts railway authorities, and slows down trains if an animal remains on the track.
With ML: Cameras capture images at intervals and run an ML model to detect animals.
If an animal is detected for more than 2 minutes, the system triggers alerts and actions.
If an animal is detected and a train is within 5km, an alert is sent to the nearest railway station and the train driver.
A buzzer near the camera activates to scare the animal away.
If the train is 5km away and the animal is still on the track, the train’s speed is slightly reduced.
If the train reaches 2km and the animal is still there, the train gradually slows down further to prevent a collision.
Railway Dashboard: Displays alerts from multiple cameras.
Train Dashboard: Allows drivers to see alerts and the next camera's status.
Voice Alerts: Instead of relying on visual warnings, voice notifications will inform train drivers to minimize distractions.
API to fetch real-time train location.
API to calculate distance between the train and the camera.
API to check camera and nearest station.
Rail Kavach differentiates itself by using fixed remote cameras along the railway tracks instead of mounting detection systems on moving trains. Unlike traditional train-mounted animal detection, which has a limited field of vision and reaction time, Rail Kavach’s static cameras provide real-time monitoring over a larger area, ensuring that animals are detected much earlier. This allows for gradual speed reduction, better warning systems, and increased safety margins, making it a more effective and proactive solution for preventing railway accidents.
Government & Railway Contracts – Collaborate with railway authorities for large-scale deployment.
Subscription-Based Monitoring Services – Provide railway operators with AI-powered monitoring and alert services.
Hardware Sales & Installation – Sell and install cameras, sensors, and buzzer systems.
Data & Analytics Services – Offer insights and reports on wildlife movement, train safety, and track monitoring.
Maintenance & Support Contracts – Annual contracts for hardware servicing, software updates, and system monitoring.
International Expansion – Partner with global railway networks in wildlife-sensitive areas.
According to the Wildlife Institute of India (WII), thousands of wild animals, including elephants and deer, are killed annually due to train collisions.
Indian Railways reported over 200+ train-animal collisions per year, causing significant financial losses and service disruptions.
Global railways, including those in the US, Canada, and Australia, face similar challenges in wildlife-rich zones.
Governments worldwide are pushing for AI and smart railway solutions, creating a market for intelligent railway safety systems.
During the hackathon, we built a working prototype of Rail Kavach, focused on early animal detection and real-time alerting. We trained and integrated a custom YOLO-based ML model with 85% accuracy to detect animals on the track using camera feeds. If an animal remains for over 2 minutes, the system triggers alerts, activates a buzzer, and updates the dashboards. We developed a mobile alert system app to notify nearby stations and train drivers in real time. Using physics-based formulas, we dynamically calculate the safe braking distance based on train speed, ensuring timely and effective speed control. The dashboards, built using Next.js, show live camera alerts and train info. Our backend, developed with Node.js and REST APIs, handles detection logic, alerts, and data flow. We also addressed connectivity and power issues by simulating offline handling and proposing solar-powered edge devices for remote areas.