IoT Testing Services for Telematics App

Behind the telematics app car insurance testing

Project

The client is an insurance company from the UK working with fleet and logistics companies. Since drivers are often careless about their behavior on the road, the client decided to create a separate service that would monitor road incidents and accidents. It will help the company optimize its insurance packages. The Cubit Insurance turned to Euristiq for the IoT testing services for their telematics app.

Location
Europe
Industry
Fintech
Service line
Quality assuracne
IoT Testing Services for Telematics App Car Insurance
Services:
  • Cloud computing
  • IoT
  • A decision on the technical stack
  • Architecture engineering
  • UI/UX design
  • Front-end/back-end development
  • QA
  • Product management
  • SaaS deployment
  • Technical consulting
  • Requirements elaboration
Technologies:
  • PostgreSQL
  • HTML/CSS
  • JavaScript
  • Google Maps
  • Java
  • Angular
  • DDD
  • AWS
  • AWS SQS
  • AWS API Gateway
  • AWS Fargate
  • AWS RDS
  • AWS Cloudfront
  • AWS CloudFormation
  • AWS CodePipeline / CodeBuild / CodeDeploy
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Challenge

Navigating the maze of telematics testing and driver behavior monitoring challenges

The idea was to install video recording devices that record the environments both inside and outside the car. The devices have various sensors, including GPS, crash sensors, etc. The data collected by the device will serve as an actionable insight for the company to act on.
The task of the Euristiq team was to design a Cloud system that would process the data from the devices and collect information on the driver’s behavior on the road (driving skills, car condition, etc.).

After the assessment of the project, we identified key testing goals. In this case, we had hardware represented by the camera. We connected it to the vehicle and performed real-world testing to ensure it worked as the client intended. We aimed to check the following:

  • How the camera generates data and whether it is accurate
  • How the data is logged
  • How the data is processed and visualized for the user

To perform such testing, the skills of driving license and the experience of working with data logs and databases.

Solution

Power of IoT testing techniques for telematics app and driver behavior monitoring

In the testing process, we found some critical bugs in the functionality of the selected hardware. To be specific, the data logging and accuracy issues.

The other challenge we encountered was related to the described manufacturer’s capabilities of the camera, which appeared to be unavailable. After contacting the producer, we established that some settings are on paper but not working efficiently in practice, and the manufacturer won’t be able to fix them. Hence, it should be treated as a limitation caused by the hardware. For example, the camera was supposed to react to change in acceleration. As per the manual, acceleration was categorized into three types low, medium, and high. However, they were not defined, so it was unknown what the camera considers a medium-acceleration.

Finally, the camera uses third parties, and it was essential for us to understand the cost of it. In our case, the video from two cameras was recorded to a flash drive and sent to the cloud using mobile Internet. The file size was the least favorable, leading to a high Internet bill. However, we managed to identify this issue early, to inform the client about the potential expenses.

Impact

Our QA team tested the software and hardware to ensure it met the client’s requirements. We tested the telematics system in its operational environment and confirmed it was reliable and could perform under various conditions like bumps or collisions. Additionally, we identified the areas that might cause additional expenses, e.g., the Internet bill. Testing helped the client see the software from the end user’s perspective. Hence, they could decide on the improvements or extra features that are needed or not needed depending on the future uses of the system.

After implementing real-time messages
events can be categorized quicker and more efficiently. Monitoring users are less likely to miss the events in the system. Insurance company money losses could be reduced.
By maintaining dynamic location handling
(start/end of the trip by checking the vehicle speed and user behavior) we improved the tracking experience
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