This project is an implementation of a self-driving car using deep neural networks and IoT devices. The project uses hardware and software components, including Raspberry Pi, Raspicam, Arduino Uno, Microcontroller, 4 DC motors, along with software technologies like machine learning, deep neural networks, and OpenCV. This document explains the end-to-end process of this project.
Table of Contents Project Overview Hardware Components Software Components Project Description Project Overview
The goal of this project is to develop an IoT project that automates driving for the elderly and handicapped using object detection techniques like road lanes, traffic lights, and signs. The project uses deep neural networks and machine learning algorithms to identify and track objects in real-time. The project is implemented on Raspberry Pi, Microcontroller Raspicam 5mp, ArdinoUno, and programmed in C++.
Hardware Components
Raspberry Pi Raspicam 5mp Arduino Uno Microcontroller 4 DC motors
Software Components
C++ Programming Language OpenCV Machine Learning Deep Neural Networks
Project Description
This project is an implementation of a self-driving car using deep neural networks and IoT devices. The car is equipped with a Raspicam 5mp camera that captures real-time images of the road. The images are processed using OpenCV, machine learning, and deep neural networks to detect road lanes, traffic lights, and signs. The detected objects are then tracked in real-time, and the car's movements are adjusted accordingly.
The project is implemented on Raspberry Pi, Microcontroller Raspicam 5mp, ArdinoUno, and programmed in C++. The car's movements are controlled by 4 DC motors, which are connected to the microcontroller. The microcontroller communicates with the Raspberry Pi using a serial communication protocol.
In summary, this project is an innovative application of deep neural networks and IoT devices to automate driving for the elderly and handicapped. The project has the potential to revolutionize the transportation industry and improve the lives of millions of people worldwide.