An Easy-to-Set-Up GPS Tracker for Raspberry Pi Users!

What is your project about?

Our project is an Easy-to-Set-Up GPS Tracker for Raspberry Pi users. Using a Raspberry Pi 4 8GB and a 4G LTE EG25-G HAT, the GPS Tracker can monitor location in real-time. What makes it unique is that it's powered by the AI Agent Host, an evolving platform designed to support future AI features.

Why did you decide to make it?

The idea behind creating this GPS Tracker was to showcase the versatility and capabilities of the AI Agent Host as a powerful development environment. While the GPS Tracker itself provides valuable real-time data on location, it's just the tip of the iceberg. The AI Agent Host has the potential to support much more complex AI and machine learning tasks, serving as an extensible platform for future projects.

How does it work?

The GPS Tracker is remarkably user-friendly and requires minimal setup. As a result, the GPS Tracker is essentially ready to use out-of-the-box. All you need to do is connect the 4G LTE EG25-G HAT to your Raspberry Pi with the UART interface, and the AI Agent Host takes care of the rest. Your Grafana dashboard will start displaying real-time data on location almost instantly after running the Python script for data stream processing.

The AI Agent Host, when combined with the 4G LTE EG25-G HAT for Raspberry Pi, allows you to create a GPS tracking system without the need for external tracking services or server/client setups. The AI Agent Host provides a versatile platform for running and managing your Python scripts and applications, while the 4G LTE EG25-G HAT enables GPS tracking and communication via 4G, 3G, and 2G networks.

By leveraging the AI Agent Host's capabilities, you can run your GPS tracking script directly on the Raspberry Pi, visualize the tracking data on Grafana, and even make modifications to the code using the Code Server interface. This self-contained solution eliminates the dependency on external tracking services and provides you with full control over the tracking process and data visualization.

In essence, the combination of the AI Agent Host and the 4G LTE EG25-G HAT empowers you to create an end-to-end GPS tracking system within your own environment, making it a powerful and flexible solution for tracking applications.

Getting Started

It will take approximately 15 minutes to install DietPi and another 15 minutes to install the GPS Tracker.

1. Set Up Parameters:After installing the AI Agent Host, open VS Code in your browser through an HTTPS connection. Navigate to >project/vehicle-tracking/data-stream-processing.py.The script is pre-configured to connect to a QuestDB instance using the following credentials:

conn = psycopg2.connect(
    dbname="qdb",
    user="admin",
    password="quest",
    host="yourdomain.tld",
    port="8812"
)

Remember to replace <yourdomain.tld> with the actual domain name that points to the IP address of the Fixed IP SIM Card where your Raspberry Pi is running.

2. Run Python File in Terminal:Execute the Python script from the terminal to start collecting GPS data data.

3. Connect to Grafana Dashboard:Open your browser and navigate to the Grafana interface. Select the GPS Tracker dashboard to start monitoring your data in real-time.

4.Customizing the GPS Tracker:

While the pre-configured GPS tracker setup is designed to work out of the box, you can also customize it to match your unique requirements. Here are some steps to consider when customizing the setup:

• Modify Data Stream Processing: The Python script responsible for processing GPS data can be customized to include additional data points or calculations. For example, you could include data related to vehicle speed, direction, or any other sensor readings.
• Enhance Grafana Dashboard: The Grafana dashboard can be tailored to display the additional data points collected from the GPS tracker. You can add new panels, visualizations, and filters to create a dashboard that provides valuable insights for your specific use case.
• Integrate with External Services: If you have specific external services or APIs you'd like to integrate with, you can modify the Python script to send data to those services. This could include data storage in cloud platforms, real-time alerts, or other notifications.
• Fine-Tune GPS Accuracy: Depending on your tracking needs, you can explore ways to improve GPS accuracy, such as fine-tuning the frequency of data collection, incorporating more advanced GPS modules, or implementing data filtering algorithms.
• Advanced Analytics: If you're looking to extract advanced insights from the collected GPS data, you can incorporate data analysis techniques, machine learning models, or predictive analytics to derive valuable information from the tracker's data stream.