TechHive 
FleetSmart Fleet Optimisation Platform
A leading innovator in commercial vehicles — trucks, buses, vans, and engines — with a strong focus on electric mobility and autonomous vehicle technology.
Technologies Used
The Challenge
As the client's fleet grew, disconnected tools were slowing everything down — fragmented data collection, delayed maintenance interventions, and suboptimal route planning. Existing systems couldn't support real-time analytics or scale to future technology, even as pressure mounted to cut downtime and improve efficiency.
The Solution
We built an integrated fleet platform starting with IoT sensors streaming engine diagnostics, fuel data, and GPS location over MQTT into a standardised format. Apache Spark handled batch processing and Apache Kafka handled real-time streams, feeding a predictive maintenance engine trained on three years of historical data and validated across 500 vehicles at 92% predictive accuracy. The whole system runs on a scalable, cloud-native AWS architecture (Lambda, DynamoDB, S3) with built-in redundancy, fronted by a React.js dashboard giving fleet managers live updates, custom reports, and predictive insights at a glance. Jenkins and Kubernetes kept releases fast and reliable, end-to-end encryption and role-based access protected fleet data, and the platform was stress-tested for scale up to 20,000 vehicles — all delivered in close collaboration with the client's own fleet and IT teams.
The Results
- 30% less vehicle downtime through proactive maintenance and real-time issue detection.
- 25% better fuel efficiency and delivery schedules from route optimisation.
- 15% lower maintenance costs via early fault detection.
- 40% more operational visibility, sharpening fleet managers' decision-making.
- Built to scale — new devices and capabilities integrate smoothly as the fleet expands.
- Delivered in a phased 12-month rollout, with incremental releases enabling early testing and adaptation.