ESP32 Estimate Velocity with GPS MPU6050 Dead Reckoning

Advanced navigation project combines NEO-M8N GPS module, MPU-6050 6-axis IMU, and ESP32 to estimate velocity with higher accuracy than GPS alone using sensor fusion. When GPS signal lost (tunnel, garage), MPU-6050 accelerometer data integrated over time (dead reckoning) estimates position and velocity. Kalman filter fuses GPS velocity and IMU-derived velocity for smooth accurate output. MPU-6050 bias calibration runs at startup. GPS at 10Hz update rate via UART. Fused velocity, heading, position, and acceleration logged to SD card (CSV format) and displayed on 2.4-inch TFT with live speedometer gauge. Web dashboard shows real-time track on OpenStreetMap. Libraries: TinyGPS++, MPU6050_tockn, Kalman, SPI, SD, TFT_eSPI.

Detailed Project Description

ESP32 Estimate Velocity with GPS MPU6050 Dead Reckoning records position/motion data over time and presents it as a track or log that can be reviewed later.

How It Works
1. The positioning sensor provides coordinates/motion at a fixed rate.
2. Points are filtered and stored (SD card, cloud or database) with timestamps.
3. A map or chart renders the track; live position can be viewed remotely.
4. Geofence or speed alerts are optional.

Key Components and Their Role
- ESP32: dual-core Wi-Fi + Bluetooth microcontroller that runs the firmware, reads the sensors and hosts the network connection.
- MPU6050: 6-axis accelerometer + gyroscope IMU used for motion, tilt and gesture sensing.
- TFT display: colour graphical display (SPI) used for the on-device user interface.
- GPS module (NEO-6M): receiver that provides latitude, longitude, speed and time over UART/NMEA.
- microSD card module: storage for logs, audio or images over SPI.

Implementation Steps
1. Collect the components and study each module's datasheet (pin-out, voltage, interface).
2. Wire the circuit on a breadboard following the pin mapping; power sensors from the correct rail (3.3 V / 5 V).
3. Install Arduino IDE, TinyGPS++ Library, MPU6050_tockn Library and the required libraries; flash a minimal test sketch for each module separately.
4. Write the main firmware: read sensors → process → drive outputs / send data.
5. Configure network or cloud credentials and test communication end-to-end.
6. Calibrate thresholds, add error handling (reconnect, sensor time-out) and run a long-duration test.
7. Finalise on a PCB / enclosure and document wiring, code and results.

Key Features
- Live location
- Track history
- Map view
- Alerts

Expected Output
On completion the student will have a map trace of where the device has been, with speed and time for each point.

Deliverables
- Complete source code with comments
- Circuit diagram and pin mapping
- Project report with screenshots and results
- Demonstration-ready build