Autonomous Agricultural Rover with AI Plant Disease Detection & Precision Spraying
IEEE Robotics Project. Raspberry Pi 4 vision-guided rover detecting foliar diseases via MobileNetV2 with GPS waypoint navigation.
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Project Technical Overview
Full-scale autonomous agricultural platform powered by Raspberry Pi 4, MobileNetV2 CNN classifier running on OpenCV/TensorFlow Lite, high-torque NEMA 17 stepper drive system, GPS neo-6m, and solenoid-valve relay spray system. ### Practical Student Engineering Solution Fully functional hardware demonstration prototype equipped with dedicated microcontrollers, precision sensors, actuators, and an interactive cloud/mobile telemetry dashboard. ### Key Learning Outcomes - Embedded C / MicroPython firmware architecture and sensor interfacing - IoT telemetry protocols (MQTT / HTTP / BLE / LoRaWAN) - Power regulation, hardware debugging, and PCB design principles - Comprehensive technical documentation aligned with IEEE academic standards
Read the foundational IEEE conference research paper, citations, and algorithmic architecture for this project.