- Cloud solutions
- Maps and Geolocation
- Frontend
- Backend
- DevOps
- IoT
- Optimization
- Real Time Solution
Development of a GPS fleet tracking solution that uses the Internet of Things (IoT) data to provide visibility into whatâs happening on the road in real time and allow interventions even if the truck is thousands of miles away. Optimizing the systemâs code and improving its integration capabilities so it can display up to 1000 trucks on a map simultaneously and visualize their movements in real time.
client
3D Telematics
Malaysia
Up to 50 employees
A GPS fleet tracking company and logistics software provider that offers a web and mobile-based solution for managing and streamlining the workflow of multiple fleet operators on a single platform.
request background
Implement a GPS fleet tracking system based on a proof-of-concept
Development of a GPS fleet tracking solution that uses the Internet of Things (IoT) data to provide visibility into whatâs happening on the road in real time and allow interventions even if the truck is thousands of miles away. Optimizing the systemâs code and improving its integration capabilities so it can display up to 1000 trucks on a map simultaneously and visualize their movements in real time.
challenge
A testing prototype of a GPS tracking app that had low flexibility, limited integration capabilities, and no documentation
The Malaysian provider of fleet tracking services approached us with a PoC that was completely undocumented. To begin with, all we had was the product vision, a basic web-based application with some testing data to demonstrate how the future GPS fleet tracking software solution should work, and certain documentation provided by producers of IoT devices we had been integrating the clientâs solution with.
After we conducted a thorough audit of the clientâs fleet management and tracking app, (just as we did in the web-based shipping platform project), we noticed that it had two significant limitations. First, the poor code quality hampered new feature implementation. Second, the existing integration mechanism wasnât stable enough to allow hundreds of trucks to be connected to the system and displayed on the map simultaneously with real-time movement visualization as the client required.
The client couldnât achieve their goals using the existing codebase. After all, the provided app was more of a concept rather than a fully-fledged GPS telematics fleet tracking software product that needed a couple of updates. This meant we needed to rewrite most parts of their app from scratch.
goals
- Code optimization of the clientâs app to make new feature implementation easier.
- Upgrading the integration mechanism of the clientâs solution to increase the number of IoT devices integrated by the system and visualized on a map.
- New feature implementation, such as remote vehicle control and real-time freight movement visualization
solution
The transforming power of technology and expertise
Node.js, PHP, HTML, CSS, AWS
2 years- 3 specialists
First of all, we improved the integration capabilities of the clientâs GPS fleet management solution using a Node.js-based IoT signal parser. This allowed us to dramatically increase the number of connected devices. Second, we optimized the backend code, which gave us a stable core for further development and feature implementation.
To implement functionalities for the clientâs fleet tracking system, the development team's capabilities were increased from two to three contributors. From the clientâs end, the product owner was in touch with us throughout the entire process.
As a result, this product traveled a two-year-long path from a basic proof-of-concept (PoC) with many challenges to be resolved to become one of the best fleet GPS tracking systems in the market.
The following IoT fleet tracking and management features were implemented:
- Constant data transmission. If a connected fleet tracking device is switched on, the system constantly receives a signal from it to collect the needed vehicle data, such as speed, time on the road, fuel level, GPS position, tire pressure, and video streaming from cameras.
- Reporting. All device data is stored in the system for further analysis and can be exported in preferable formats, like .csv and .pdf.
- Data visualization. The collected data can be visualized in web reports and on an interactive map. Optimized code allowed us to boost the systemâs stability, enabling us to significantly increase the number of trucks displayed on a map simultaneously. Meanwhile, the WebSocket protocol allowed for smooth map updates for real-time freight movement visualization.
- Remote command processing. The dispatcher can send a remote command to a device to perform some actions, such as switching the engine off/on, opening containers, and so on. This feature particularly comes in handy at customs. Since drivers typically donât have access to the freight and canât open containers on their own to present the goods to a customs officer for inspection, the dispatcher can open the container remotely upon the driverâs request.
outcome
From basic PoC to powerful telematics system
- AWS-based architecture with powerful data storage and processing capabilities
- Seamless integration with approximately 1000 IoT devices, including GPS trackers from different manufacturers
- New features, such as video streaming from cameras or remote command processing
- An increase in the number of trucks displayed on a map from 100 to 1000 objects
- Smooth truck movements visualization in real-time â before we stepped in, the location of trucks on the map of the clientâs GPS tracking app was updated only every 5-10 seconds
- The considerable increase in speed of automated composing of the truck movements report: from 4 days for 4 trucks to 15-40 seconds for 1000 trucks
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