The main objective of the Vision-Based Autonomous Delivery Bot using ESP32 is to design and develop a smart robotic system capable of performing autonomous short-distance delivery tasks with real-time obstacle detection and IoT-based monitoring. The system aims to integrate sensors such as ultrasonic, DHT11, and MQ135 with an IP camera to enable safe navigation, environmental monitoring, and live video streaming. It also focuses on using the ESP32 microcontroller for efficient motor control, wireless communication, and remote operation through the Adafruit IO platform. Overall, the project seeks to create a cost-effective, intelligent, and scalable delivery solution suitable for smart homes, offices, campuses, and indoor logistics applications.
This project presents a Raspberry Pi-based eye movement-controlled cursor system using OpenCV and a USB web camera. The camera continuously captures eye movements, and OpenCV image processing techniques are used to detect and track the user's gaze in real time. Based on the detected eye movement direction, the system controls the computer cursor without requiring a mouse or touchpad. The proposed system provides a low-cost, efficient, and hands-free humanβcomputer interaction solution, particularly useful for individuals with physical disabilities and assistive technology applications.
Keywords: Raspberry Pi, OpenCV, Eye Tracking, Cursor Control, Computer Vision.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

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