Learn how we delivered a complex IoT-based fleet management solution that accelerates order delivery, enables predictive maintenance, and reduces operational and utility costs.

  • Industry


  • Country


  • Team size


  • Period of collaboration

    December 2021 – present

About the client

Our client is an established logistics company that delivers goods across the US. They manage warehouses in multiple states and own a fleet of 350+ vehicles. 

Business context

Over the years, our client expanded their business presence to multiple states. However, they mostly relied on outdated management processes and an array of third-party services, which gradually were stretched beyond their capacity. The client’s team faced the following challenges:

  • Inefficient operational processes and problem-solving due to a significant amount of manual work and phone calls between operators and drivers
  • Financial losses resulting from urgent unscheduled fleet maintenance, leading to delayed order deliveries
  • Inability to monitor the fleet’s condition in real time and to efficiently plan routes for drivers
  • Decreased customer satisfaction and loss of customers due to failed orders

The client approached Yalantis to address these challenges by digitalizing business processes. With experience delivering logistics solutions, our expertise matched our client’s business requirements.

Solution overview

  • Our client asked us to develop an IoT-based fleet management solution that could seamlessly digitalize all of their processes and help them in adapting to new market requirements and customer demands. Designing the solution included several steps:

    • Integrating IoT devices into fleet operations
    • Developing a multi-interface solution for monitoring and managing devices and the fleet
    • Automating paper- and call-based processes and communication
    • Implementing predictive maintenance for cost reduction
  • Selecting parameters to measure with IoT sensors

    Throughout the discovery phase, our business analysts identified critical parameters that would enable the client to gather essential information about the fleet’s condition. During the device selection process, they considered the vehicle models used by drivers.

    As there were multiple parameters to measure and, consequently, sensors to use, Yalantis’ software engineers also helped to design a prototype of an IoT device equipped with multiple sensors. They used 3D printing technology to save resources. After the prototype was ready, our client found a vendor for mass production.

    As a result of this phase, to enable all-around monitoring of fleet’s conditions, our team selected sensors for tracking:

    • Geolocation
    • Tire pressure
    • Speed
    • Motion and vibration 
    • Motor temperature 
    • Objects (using object recognition)
    • Proximity 
    • Load 
    • Environmental temperature 
  • Designing the solution’s architecture to cover all business needs

    While designing the solution’s architecture, our software engineers ensured it was able to collect streaming data, serve a diverse range of devices, and perform complex real-time big data analytics. To enable this, they opted for a microservice architecture that allows for seamless modifications to various solution components without affecting the whole system. 

    The development team chose AWS as a cloud provider due to its scalability opportunities and comprehensive set of tools that were also selected for managing IoT devices:

    • AWS Kinesis for managing streaming data in large volumes
    • AWS Lambda to ensure smooth and effortless infrastructure management
    • AWS IoT Core to ensure secure and real-time device-to-cloud communication
    • AWS IoT Defender for device monitoring, anomaly detection, notification, and mitigation
    • AWS IoT Fleet Hub to monitor the health of IoT devices in real time
  • Establishing extract, transform, and load (ETL) data processes 

    Yalantis’ software engineers established streamlined data processes with the help of: 

    • AWS IoT Analytics, a set of tools that helps collect data from devices and process it for further customization and analysis
    • Amazon QuickSight, a cloud-based business intelligence and data visualization tool that later aided us in providing the client’s analysts with dashboards and data charts
    • Amazon S3 Buckets to ensure reliable and scalable SQL-based data storage
    • AWS Lake Formation to manage business processes involving large amounts of data

    To enable uninterrupted data streaming, the client used eSIMs for cellular data to connect devices with the cloud.

  • Making data work for the client through predictive analytics and complex fleet maintenance

    To facilitate fleet management, the Yalantis team established comprehensive data-based processes that reduce maintenance costs and enable real-time monitoring of fleet conditions. To achieve this goal, our solution development team employed the Yalantis IoT Accelerator and:

    • configured data collection, processing, and analysis
    • ensured real-time big data analytics using AWS IoT services, enabling our client to stay informed about device and fleet conditions as well as to monitor order deliveries
    • set up thresholds indicating normal, alarming, or critical conditions for both devices and the fleet
    • implemented machine learning (ML) algorithms that identify potential issues based on thresholds and trigger alerts for staff
    • deployed predictive analytics based on data collected from devices and analyzed with AWS tools, notifying about the need for pre-scheduled vehicle maintenance
    • developed a sophisticated BI module to identify processes and operations causing financial losses and those that help our client save resources
  • Building multiple interfaces for different user roles

    There are several parties involved in warehouse and fleet management on the client’s side. That’s why multiple interfaces were developed by Yalantis’ engineers catering to different access roles and rights:

    • A web BI panel for visualizing data on dashboards and analytical reports
    • A mobile application for drivers, providing e-logging, route specifications, notifications, salary calculation, and chat functionality for communication with operators
    • A web panel for clients to make orders and monitor shipment statuses 
    • A web support team interface with access to the client’s database enabled through Salesforce integration for communicating with drivers and clients and monitoring order delivery
  • Development results: Functionality that covers essential operational needs

    The development team provided functionality that will aid in digitalizing all paper-based and resource-intensive processes. Our objective was to enhance overall operational and business efficiency while creating a user-friendly working environment for our client’s employees. The results include:

    • Easy-to-use dashboards that enable real-time monitoring of delivery statuses, deadline compliance, completed deliveries, and regional and branch statistics for the client’s company. Operators can also see any delivery issues or delays on the dashboard and respond promptly.
    • A comprehensive notification center that provides real-time notifications to all involved parties, including operators, managers, drivers, security, and support teams. Data from sensors in drivers’ vehicles helps analyze the current vehicle condition and the system instantly notifies both drivers and operators via the dashboard.
    • A route planning module that assists operators in creating optimal route drafts for drivers based on specific delivery requirements.
    • A radio communication channel that simplifies communication between operators and warehouse managers, integrated with MOTOTRBO Radio Management for two-way digital communication.
    • An admin panel for managers to assign roles and responsibilities, manage access, and receive weekly and monthly reports on warehouse operations and fleet management.
    • Route planning: With Onfleet integration, operators can design routes for drivers in just a few clicks, easily providing the best routes considering factors such as distance, load, location type, number of turns, and stops.
    • Notifications: We built an event- and trigger-based notification system that automatically notifies responsible teams when there are any issues or delays in the solution’s operation. This ensures timely issue resolution and risk mitigation.

Value delivered

Yalantis continues to diligently refine the solution. Thus far, we have contributed to achieving the following goals:

  • 1.5X faster order delivery. With automatic and more efficient route planning, drivers can embark on their journeys earlier and use shorter routes compared to manual planning. Real-time data from sensors informs a driver of their vehicle’s condition.

  • Up to 40% reduction in operating costs. Predictive analytics enables dynamic fleet maintenance, saving resources on unexpected and large-scale repairs. Efficient route planning reduces expenditures on fuel. And implementing BI helps the client identify unnecessary spending on and digitalize internal processes.

  • 50% greater operational efficiency. We helped our client digitalize nearly 90% of processes and eliminate paper-based workflows. Employees now complete forms with a few clicks, allowing them to immediately progress to the next task.

  • Optimized communication. We eliminated the need for personal communication between drivers and operators with the help of a notification center. Operators can resolve issues before they become critical problems.

  • Real-time analysis of fleet conditions. With real-time analytics and predictive maintenance, operators, drivers, and maintenance specialists can identify and address potential issues while staying updated about the fleet’s status.

  • Advanced functionality for sleep prediction. This feature is currently in development. We are now working on the proof of concept and testing its capabilities.


Yalantis will help roadmap your fleet management processes with IoT technology and set up complex data analytics processes for real-time fleet monitoring and dynamic maintenance.

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