Track Vibration & Stress
Deploys low-power acoustic vibration and thermal sensors along track sections to detect structural micro-fractures in real time.
Innovation · 1st Place SIH Winner
Surya-
Pathik.
National award-winning AI + IoT hardware-software ecosystem designed for real-time track anomaly detection and railway safety.
1st PlaceSIH National Award
AI + IoT Hardware & UXDigitAlly Scope
<800msAlert Latency
1.5 kmSafety Buffer
The Challenge
A critical safety question, tackled at pace under real hackathon pressure.
Track maintenance and obstacle detection on high-speed rail corridors historically relied on periodic physical trackman patrols, creating dangerous blind spots between patrol intervals.
The challenge was to design and prototype a real-time monitoring solution capable of detecting millimeter-scale track shifts, thermal expansion stress, and physical track obstacles—and instantly alerting oncoming locomotive drivers before entering the risk zone.
Project Recognition
Validated at national scale.
1st PlaceSmart India Hackathon (SIH)
<800msTrack-to-cab alert dispatch latency
1.5 kmAutomated locomotive safety buffer
24/7Telemetry dashboard UI & hardware prototype
System Design
Connected hardware & high-clarity software.
Real-Time AI Processing
Runs lightweight anomaly classification models on edge microcontrollers to filter false positives before transmitting alerts.
High-Contrast HUD
Designed a high-urgency driver cockpit display giving clear visual and auditory distance-to-hazard indicators.
Control Room Telemetry
Provides central railway controllers with a live map overview of track health, maintenance schedules, and automated incident logs.
Explore All Selected Work