Challenges
The client’s dispatch team did not have a consistently updated view of its fleet. Existing GPS systems sometimes returned delayed or inconsistent location information, making it difficult to know where vehicles were and respond quickly when delivery conditions changed.
These gaps affected coordination between drivers, dispatchers and other operational teams.
Route planning also depended heavily on manual work. Routes prepared at the start of a journey could become less effective when traffic congestion, road closures, construction or weather conditions changed.
Without a practical way to recalculate routes, drivers could experience avoidable delays while dispatchers spent additional time reorganising assignments.
Communication created another operational challenge. Drivers and dispatch teams did not always receive synchronised updates, which could lead to uncertainty around route changes and job allocation. The company needed a shared operational view where dispatchers could follow current activity and drivers could report issues from the road.
Fleet information was also distributed across separate systems. Live location feeds, historical records and operational data could not be reviewed together easily, limiting the company’s ability to monitor performance through consistent KPIs.
At the same time, any automated alert system had to avoid overwhelming dispatchers with low-priority notifications.
The project therefore required more than a vehicle-tracking interface. The company needed a connected application that could standardise incoming data, support changing routes, improve communication and make live and historical fleet information available from one operational environment.
Solution
Lucent Innovation began by reviewing how GPS information entered the client's existing systems and how dispatch teams planned routes, monitored vehicles and communicated with drivers.
This review identified differences in the data formats produced by fleet sensors, which had to be addressed before location information could be used consistently.
At a system level, the application followed one connected flow: fleet devices sent data into Azure IoT Hub, which fed a transformation layer that standardised the information; this standardised data then powered route planning and alert workflows, surfaced through the operations dashboard, and was stored for ongoing reporting.
Building each part against this flow kept the pieces working as one system rather than as separate tools bolted together.
A custom data-transformation layer was developed to standardise the incoming GPS and sensor information. Azure IoT Hub received data from connected fleet devices, while Azure Functions processed events and supported the application workflows around those updates. This created a consistent flow of vehicle information for the wider system.
The route-planning workflow combined Azure Maps with the Google Maps API. Initial route information could be updated when current traffic conditions, road closures or construction affected the planned journey. Instead of relying only on routes prepared before departure, dispatchers could respond to changing road conditions while vehicles were in operation.
Lucent then developed a ReactJS dashboard using Redux and Tailwind CSS to give dispatch teams a central place to review vehicle locations, routes and operational updates in one interface. A communication module built into the same dashboard let drivers report route problems directly, so dispatchers could assess each report alongside the live fleet data already on screen.
Lucent's ReactJS developers build this kind of interactive, data-connected dashboard for operational teams that need a live, single view of their systems.
The dashboard was connected to a Node.js and Express backend responsible for coordinating application requests and supporting communication between the interface and Azure services.
This combination allowed the application to present frequently changing operational information through a structured frontend. Lucent’s ReactJS developers support similar applications involving interactive dashboards, API connectivity and real-time operational data.
Alerts and notifications were handled through Azure Logic Apps and the Twilio API. Rather than applying the same notification rules to every event, the system allowed alert preferences and thresholds to be adjusted. This helped dispatchers focus on updates that required attention without receiving unnecessary notifications throughout the day.
Lucent also created a middleware layer to connect historical information from the client’s legacy systems with the new Azure data environment. Azure Data Lake and Azure Stream Analytics supported the processing of live and historical fleet information, while Azure SQL Database stored structured application data.
Bringing these components together gave the client one application for vehicle monitoring, route planning, alerts, communication and operational reporting. Dispatch teams could work with a shared view of fleet activity instead of moving between disconnected data sources and communication channels.
