RouteEye
Real-Time Vehicle Tracking & Fleet Management
A high-frequency fleet management platform processing live IoT telemetry every 5 seconds. Built for operational precision — precise location tracking, route oversight, and real-time alerting at scale. Live at Bangalore International Airport.
// system architecture
How it Works
Vehicle IoT devices push telemetry to AWS IoT Core via MQTT. A dedicated Go device service ingests, validates, and persists the data. Redis Pub/Sub relays updates to the SSE stream layer, delivering live map state to the React dashboard in under a second.
IoT Layer
- Vehicle GPS + sensor hardware
- MQTT protocol to AWS IoT Core
- Device registry & certificate auth
- IoT Rules routing to Lambda/services
Backend Layer
- Go microservices — device service + API service
- High-frequency telemetry ingestion & write-optimised PostgreSQL
- Redis Pub/Sub for internal event relay
- JWT-authenticated REST API
Real-time Delivery
- Server-Sent Events for live map updates
- Sub-second latency from device to dashboard
- Alert engine with 9000+ events processed
- React dashboard with live vehicle markers
// platform
The Dashboard
A unified ops dashboard giving fleet managers live vehicle positions, route adherence, stop coverage, alert logs, and upcoming trip schedules — all updating in real time without a page refresh.
Real-time vehicle positions with route path overlays and stop markers. Updates every 5 seconds.
Vehicle count, active/inactive status, route assignments, and stop coverage at a glance.
9,043+ alerts tracked — speeding, geofence breaches, route deviations, and schedule delays.
Upcoming trip management with route assignment, stop sequencing, and ETA tracking.
// my contributions
Team Lead · 2 Years
I led RouteEye from blank repo to production over two years — as the principal architect, lead developer, and team manager for a squad of four. This was not a maintenance role; I was in the engine room the entire time.
System Architecture
Designed and built the core RouteEye platform end-to-end — from IoT data ingestion pipelines to real-time delivery to the browser. Evolved the system from a monolith to a microservices architecture as scale demanded.
Real-time Data Pipeline
Built a dedicated device data service handling vehicle telemetry at up to 5-second update intervals. Used Redis channels and Server-Sent Events (SSE) for sub-second data delivery to dashboards.
Scalability & Performance
Owned database scaling and continuous performance optimization across the stack. Designed for high-frequency IoT writes without degrading read latency on live map views.
Product Vision
Collaborated directly with project director Kislay Komal and senior architects to shape product direction, feature roadmap, and market fit. Translated operational requirements from BIAL into technical specs.
Team Leadership
Led and mentored a team of four developers across two years. Ran day-to-day development, enforced code quality standards, and kept delivery aligned with the product roadmap.
Client Deployment
Delivered the platform for Bangalore International Airport (BIAL) — live tracking of staff shuttle fleets across the airport campus, serving real operational needs at scale.