Mobile Application for the Live Animal Transportation Company

Background

A live animal transportation company needed a mobile application that collects sensor data from their trucks and trailers to ensure the health and safety of the animals during transportation.

The sensor data included temperature and CO2 levels, which were crucial for ensuring the health and safety of the animals during transportation. The mobile application for the live animal transportation had to run on Android tablets, communicate with a backend system in real-time, provide GPS information about the truck’s location, and run in offline mode.

Challenges

The customer faced several challenges in developing the mobile application, including:

  • Collecting real-time sensor data from the trucks and trailers,
  • Communicating the sensor data, including GPS information, to a backend system
  • Ensuring data accuracy and reliability, even in offline mode
  • Developing a user-friendly interface for drivers to use.

Solution

To overcome these challenges, we utilized the Kotlin programming language for the mobile application and C# for the backend. The project was managed using the Scrum methodology and Azure DevOps. Furthermore, we used a message broker (RabbitMQ) to handle real-time communication between the app and the backend. The backend was built with a REST API for easy integration with other systems. The mobile application was developed for Android, and was able to send GPS information about the position of the truck and run in offline mode.

The mobile application for the live animal transportation was designed with a user-friendly interface and displayed real-time sensor data for the drivers to monitor. In case the sensor data exceeded certain thresholds, an alert system was put in place to notify the driver. The data received from the temperature and CO2 sensors was used for analysis and search.

Results

The mobile application for the live animal transportation proved to be a valuable tool for the company. Real-time monitoring of temperature and CO2 levels improved the safety and well-being of the animals during transport.

The user-friendly interface and real-time data transfer improved the drivers’ performance. The app’s ability to run in offline mode and provide GPS information about the truck’s location was a major advantage. The company’s operations also improved with early detection of potential problems, reducing the risk of animal loss.

Conclusion

In conclusion, the development of a mobile application for the live animal transportation proved to be a successful solution.

The combination of Kotlin, C#, Scrum, Azure DevOps, RabbitMQ, and a REST API allowed for a user-friendly and efficient solution. The app improved the company’s operations and ensured the safety and well-being of the animals during transport by providing real-time monitoring of temperature and CO2 levels, and GPS information even in offline mode.

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