Building LivePin's Real-Time Fleet Intelligence Platform

Case Studies  ·  Fleet Management  ·  LivePin GPS Security

Building LivePin's Real-Time Fleet Intelligence Platform

RK

Romit Karmakar

Technical Lead

June 15, 2024

8 months
99.9% uptime across 6+ industries

The Challenge

Fleet operators across India needed a single platform capable of handling real-time tracking for thousands of vehicles simultaneously — across school buses, ambulances, cargo logistics, and high-security cash transit vehicles. Legacy systems couldn't scale, and off-the-shelf solutions lacked the security features required for high-value transport.

The client also needed to serve radically different verticals from one codebase: highway infrastructure operators dealing with NHAI compliance, homecare companies tracking field personnel, and taxi dispatch systems needing real-time driver allocation — all with the same underlying engine.

What We Built

We designed LivePin as a multi-tenant IoT platform built on a Machine-to-Machine (M2M) and Enterprise Mobility stack. The core architecture processes huge volumes of GPS telemetry every second, runs it through an analytics pipeline, and surfaces actionable insights to operators in near real-time.

Mobile Applications

We built native iOS and Android applications in React Native — giving drivers, operators, and field personnel a single consistent experience across devices. The apps communicate with the backend over a real-time WebSocket layer that maintains persistent connections even through patchy mobile network conditions.

Remote Engine Cut-Off

One of the platform's flagship capabilities is the remote engine cut-off — designed specifically for cash transit and armoured vehicle operators. A command issued from the web dashboard reaches the vehicle's OBD unit within seconds, disabling the engine regardless of location. This required building a reliable command delivery system with acknowledgment callbacks and automatic retry logic.

Platform Architecture

The backend is built on AWS with a microservices architecture. GPS events flow into a Kinesis stream, get processed by Lambda functions, and fan out to multiple consumers: the real-time map layer, the analytics warehouse, and the alert/notification engine. This allows each subsystem to scale independently.

Results

  • 99.9% uptime SLA maintained across the full platform
  • 6+ industries served from a single codebase: highways, cargo, homecare, taxi, delivery, and small business
  • Real-time tracking with sub-second location update latency at scale
  • Enterprise clients including GMR Highways (NHAI compliance) and DTDC (fleet billing automation)
  • Portea Medicals managing health service personnel with live dispatch