This project details the development of an Unmanned Ground Vehicle (UGV) for the remote collection of agricultural data, with the goal of enhancing precision agriculture.
The UGV is designed to collect environmental and soil health parameters and can operate remotely or autonomously. It sends real-time data to a Base Station and stores it for future analysis.
The system consists of three main components:
- The UGV's main control system is managed by a Raspberry Pi (B1).
- This single-board computer handles remote operations via a WiFi Module (B3), which enables communication with the Computer Client for remote control.
- The UGV's core is a Raspberry Pi.
- The Freenove software provides built-in functionality for remote control over Wi-Fi through a computer client.
- The Raspberry Pi manages this remote operation.
- Integrated into the UGV's chassis and controlled by an Arduino Nano (A1).
- Acts as the central hub for data acquisition, collecting data from various sensors including:
- Sensors (A2): Humidity, Temperature, Soil Moisture
- NPK Sensor: Measures Nitrogen (N), Phosphorus (P), Potassium (K)
- GPS Module: Provides real-time GPS coordinates of the UGV
- An NRF24 Transmitter (A3) sends the collected sensor data, including NPK and GPS values, to the Base Station.
- The Base Station receives and processes the data transmitted by the UGV.
- An NRF24 Receiver (C1) receives data from the UGV's transmitter.
- The data is then:
- Visualized on a dashboard using Matplotlib (C2)
- Archived in CSV files (C3) for future reference and analysis
-
- Serves as the remote control interface (D1).
- Enables a user to control the UGV via WiFi communication.
- Autonomous Navigation: GPS-based path planning to reach predefined coordinates.
- Remote Control: WiFi client interface for manual operation.
- Real-Time Data Collection: Soil and environmental parameters including NPK values.
- Data Visualization: Real-time dashboard for monitoring soil health.
- Data Storage: Data archived in CSV for later research and analysis.
- Scalability: Architecture allows additional sensors or communication modules to be integrated.
- Modular Design: Independent modules (UGV, sensors, base station) make upgrades simple.
- Open-Source Friendly: Uses Arduino, Raspberry Pi, and Python libraries for easy reproducibility.
- Raspberry Pi (with WiFi capability)
- Arduino Nano
- NRF24 Transmitter/Receiver Modules
- Soil Sensors: Moisture, Temperature, Humidity
- NPK Sensor
- GPS Module
- UGV Chassis with Motors and Motor Driver
- Python 3.x
- Matplotlib
- Arduino IDE
- Raspberry Pi WiFi libraries
- Setup Raspberry Pi
- Install Python and required WiFi libraries.
- Upload Arduino Code
- Flash Arduino Nano with sensor acquisition + NRF24 communication code.
- Deploy UGV
- Run the Raspberry Pi control scripts for manual or autonomous operation.
- Run Base Station
- Launch the visualization dashboard to view live data.
The Base Station dashboard shows real-time graphs of:
- Soil Moisture
- Temperature
- Humidity
- NPK Levels
Graphs are generated using Matplotlib and updated as new data arrives.
- Data is logged and archived in CSV format.
- Suitable for:
- Historical tracking
- Precision agriculture research
- Machine learning model training
- Integration with IoT cloud platforms (AWS IoT, Node-RED, ThingsBoard).
- Machine Learning for predictive soil health insights.
- Solar-powered UGV for extended autonomous operation.
- Edge AI on Raspberry Pi for on-device decision making.
- Integration with mobile app for easier farmer access.
Read More About The Project Here : https://github.com/ujwalwag/UGVRECON/blob/main/docs/Ujwal_Waghray_Culminating%20Experience.pptx