IOT Fleet Management Solution

STEP, an innovative Software As A Service company, wanted to bring IOT and machine learning to solve logistics challenges. They required a platform for real-time vehicle tracking, idle time calculation, and delivery predictions to help control cost, boost efficiency, and optimize operations. 

  • IoT Platform
  • Azure IoT
  • Power BI Integration
  • Cloud Consulting

The Challenge


STEP managed 20,000 orders a month in various ports across India, handling various workloads like raw materials, grains, temperature-controlled goods, and other export items. They wanted to allocate vehicles efficiently to minimize expenses and track real-time vehicular movement to improve predictability and efficiency. STEP aimed to optimize workflow, reduce delivery time, and improve operations, by collaborating with InovarTech as their IoT (Internet of Things) and Azure implementation partner; to create a predictive fleet management solution.

    The Solution

    Inovar’s IOT and Cloud Consulting service team helped plan a robust and scalable IOT platform using Microsoft Azure. The three-pronged solution had the following components. We equipped them with a planet-scale solution integrated with Azure IoT Hub, Microservices, stream analytics and PowerBI to bring all the stakeholders onto the same platform. With vehicle-mounted rugged devices and integrations, we obtained vehicle speed, idle time, trip details, and real-time GPS tracking. With the QR code, we devised a solution that helped us get accurate timing for each activity. This helped in gaining insights and possible process improvement for increased efficiency.


      Intelligent Insight and Automation

      Our Big Data Consultants worked with the team to improve their workflow. Automated Scheduling helped reduce idle time and ensured accurate dispatch of trucks. Predictive Maintenance helped predict maintenance requirements and loss of revenue. Intelligent Insight helped capture data about the delivery process, for accurate delivery estimates and prevent delays.



      The solution started managing 700+ vehicles with 1 million events per day with real-time alerts. It came along with reduction in errors and downtime by 35% within the first quarter of the launch. Onboarded 100+ fleet operators, weight bridge partners, warehouses, and other traders. Improved average delivery time by 15% for deliveries. 50% cost reduction in manual efforts.

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