A mid-sized logistics and fleet management company was facing increasing operational inefficiencies due to limited vehicle visibility, unpredictable maintenance issues, and poor route optimization. By investing in a custom IoT solution — from sensor integration to cloud analytics — they achieved real-time tracking, predictive maintenance, and smarter logistics planning.
The Challenge
- No real-time visibility into vehicle location or engine health
- High fuel consumption and unoptimized routes
- Reactive maintenance leading to unplanned downtime
- Fragmented data across manual logs, spreadsheets, and isolated apps
The Solution
The company partnered with an IoT engineering firm to design and deploy a complete IoT solution covering:
Edge Device Development
- Designed custom vehicle-mounted IoT hardware with GPS, accelerometer, fuel sensor, and OBD-II interface
- Developed embedded firmware for real-time data acquisition and communication
Cloud Platform & Data Pipeline
- Built a scalable IoT cloud backend using AWS IoT Core and DynamoDB
- Developed streaming analytics to process and visualize telemetry in real time
- Added predictive maintenance algorithms using ML models trained on sensor data
User Dashboard & Mobile App
- Created a web and mobile dashboard for dispatchers and fleet managers
- Provided features like live tracking, driver behavior analysis, alerts, and reports
The Results
- Real-time location visibility for 100% of the fleet
- 35% reduction in unplanned vehicle downtime through predictive maintenance
- 25% fuel savings through optimized routes and driving behavior analytics
- Actionable insights led to better load planning and driver accountability
- Improved SLA adherence and customer satisfaction through on-time deliveries
Key Takeaway
IoT isn’t just about connected hardware — it’s about connected decisions. With an end-to-end IoT platform, the logistics firm transformed from a reactive operator into a proactive, data-driven business ready for scale.
