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🚗 CarTrack - IoT-Based Vehicle Tracking App

CarTrack is a mobile application developed in the context of the course IR2157 - Mobile Networks and Devices from the Bachelor’s Degree in Robotic Intelligence at Universitat Jaume I. This project demonstrates the integration of mobile networks, IoT devices, and Android app development to enable real-time vehicle tracking.

Developed as part of a team project, CarTrack uses Firebase and GPS/GSM-enabled IoT hardware (ESP32 TTGO T-Call) to track and manage vehicles via a real-time Android interface.


📱 App Features

  • 🔐 User authentication via Firebase
  • 📍 Real-time GPS tracking on an interactive Google Map
  • 🚙 Management of multiple vehicles and associated IoT devices
  • 📊 Location history visualization
  • 🛠️ CRUD operations for vehicles/devices
  • 🔄 Real-time synchronization using Firebase Realtime Database and Firestore

🌐 System Architecture

CarTrack follows a modular IoT architecture:

  1. IoT Device: ESP32 TTGO T-Call with GPS/GSM sends location data to Firebase.
  2. Firebase Backend:
    • Realtime Database for live updates
    • Firestore for persistent storage
    • Storage for vehicle images
  3. Android App: Visualizes locations, manages devices, syncs with backend.

🧠 Learning Outcomes

  • Developed a full-stack IoT system integrated with Android and Firebase.
  • Worked with GPS and GSM hardware in real-world mobile contexts.
  • Applied knowledge of mobile network protocols and cloud-based data management.
  • Implemented real-time location tracking, map rendering, and user authentication.

🛠️ Technologies Used

  • Android Studio
  • Firebase (Auth, Realtime DB, Firestore, Storage)
  • Google Maps API
  • ESP32 TTGO T-Call (GPS + GSM)
  • Arduino IDE (for device programming)
  • Java (main app language)

🧪 Development Highlights

  • Focused on modularity: Android app developed separately from IoT firmware.
  • Implemented sync logic between Firebase Realtime Database and Firestore.
  • Achieved location latency of ~3 seconds and accuracy within ~5 meters.
  • Designed for scalability and usability across individual users and small fleets.

📘 Course Context

Subject: IR2157 - Mobile Networks and Devices
Instructor: Raúl Marín Prades
Degree: Bachelor's in Robotic Intelligence
Semester: 4th year, 1st semester
Project Type: Team final project (App code only)


👥 Authors

  • Max Puig Sariñena
  • Albert Gabriel Matei
  • Lucas Gabaldón Selvi

CarTrack shows how mobile networks and IoT devices can be combined into a user-friendly and scalable vehicle monitoring system. The Android app in this repository represents the front-end of a complete, cloud-connected tracking solution.

📦 Note: This repository includes only the Android application code. IoT firmware and backend setup are documented in the project report. 📄 Download the Project Report from Releases

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IoT-Based Vehicle Tracking App

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