Challenge
The client assigned us to develop an IoT-based vehicle tracking system for real-time data visualization on a map. Connected devices would update vehicle data—location, speed, fuel, driving time, and camera footage — via the CAN bus, stored in a database. The solution had to allow dispatchers to manage data, generate reports, monitor events, control devices, handle billing, and access fleet management features via mobile devices or laptops.
The client assigned us to develop an IoT-based vehicle tracking system for real-time data visualization on a map. Connected devices would update vehicle data—location, speed, fuel, driving time, and camera footage — via the CAN bus, stored in a database. The solution had to allow dispatchers to manage data, generate reports, monitor events, control devices, handle billing, and access fleet management features via mobile devices or laptops.
Solution
Our team started out by enhancing the integration capabilities of the client's GPS fleet management solution by employing a Node.js-based IoT signal parser, significantly expanding the number of connected devices. Subsequently, we optimized the backend code, establishing a stable foundation for future development and feature incorporation. These efforts facilitated the implementation of IoT fleet tracking and management features, including continuous data transmission, reporting, data visualization, and remote command processing:
Continuous data transmission ensured that active fleet tracking devices consistently provided essential vehicle data. That data included speed, road time, fuel level, GPS position, tire pressure, and live camera feeds.
Our teams made sure all the device data was stored for analysis and could be exported in .csv and .pdf formats for reporting.
The implemented data visualization features presented collected data on the in-app interactive map and in web reports.
Our code optimization strategy improved system stability, allowing more trucks to be displayed simultaneously.
We also leveraged remote command processing to allow dispatchers to control devices, including engine and container access.
Our team started out by enhancing the integration capabilities of the client's GPS fleet management solution by employing a Node.js-based IoT signal parser, significantly expanding the number of connected devices. Subsequently, we optimized the backend code, establishing a stable foundation for future development and feature incorporation. These efforts facilitated the implementation of IoT fleet tracking and management features, including continuous data transmission, reporting, data visualization, and remote command processing:
Continuous data transmission ensured that active fleet tracking devices consistently provided essential vehicle data. That data included speed, road time, fuel level, GPS position, tire pressure, and live camera feeds.
Our teams made sure all the device data was stored for analysis and could be exported in .csv and .pdf formats for reporting.
The implemented data visualization features presented collected data on the in-app interactive map and in web reports.
Our code optimization strategy improved system stability, allowing more trucks to be displayed simultaneously.
We also leveraged remote command processing to allow dispatchers to control devices, including engine and container access.
Results
Acropolium provided seamless integration with nearly 1000 IoT devices, including GPS trackers from various manufacturers.
We introduced new features like live video streaming from cameras and remote command processing to the client’s workflow.
The client expanded the map display capacity from 100 to 1000 truck objects.
The solution supports real-time visualization of truck movements with smooth transitions.
The client saw significant reporting speed optimization, switching from 4 days for 4 trucks to 15-40 seconds for 1000 trucks at a time.
Read our case study here: https://acropolium.com/portfolio/iot-based-gps-fleet-tracking-app-development/
Acropolium provided seamless integration with nearly 1000 IoT devices, including GPS trackers from various manufacturers.
We introduced new features like live video streaming from cameras and remote command processing to the client’s workflow.
The client expanded the map display capacity from 100 to 1000 truck objects.
The solution supports real-time visualization of truck movements with smooth transitions.
The client saw significant reporting speed optimization, switching from 4 days for 4 trucks to 15-40 seconds for 1000 trucks at a time.
Read our case study here: https://acropolium.com/portfolio/iot-based-gps-fleet-tracking-app-development/
