Project Title: Raspberry Pi Sensor Integration & AI Dashboard

Overview

This project involves integrating three different sensors with a Raspberry Pi, each employing distinct communication protocols. The collected sensor data is then visualized on a dashboard, along with the integration of an AI model for object detection.

Installation and Execution Guide

Prerequisites

• Raspbian Operating System
• Required Hardware Components
• Software Dependencies: Node-RED

Hardware Components

1. Raspberry Pi 4 Model B 8GB
2. Ultrasonic Sensor (US100)
3. Digital Intensity Sensor (BH1750FVI)
4. Temperature Sensor (TMP36)
5. RPi Approved Phidisk Class10 U1 MicroSD-64GB
6. MCP3008 - 8-Channel 10-Bit ADC With SPI Interface
7. Logitech USB Camera C270 Model
8. USB microSD Card Reader and Writer
9. Raspberry Pi 4 Power Switch Supply Cable USB C
10. Soldering Tools
11. Multimeter

Software Requirements

1. Raspbian Operating System
2. Node-RED

Setting Up Raspbian OS

1. Manual Installation:

   • Format SD card (FAT32)
   • Use BalenaEtcher to flash Raspbian OS onto the SD card.

2. Automatic Installation:

   • Utilize Raspberry Pi Imager for a hassle-free installation process.

3. Update Raspbian:

   • Update and upgrade Raspbian by running commands in the terminal.

Installing Node-RED

1. Execute the provided script to install Node-RED on Raspberry Pi.
2. The script will handle installation, upgrading, and service setup automatically.
3. Utilize provided commands for managing the Node-RED service.

Object Detection AI Model

• Employed an object detection model based on COCOSSD dataset for real-time object identification.
• Utilizes p5.js framework to display the model's output.

Dashboard Features

Real-Time Sensor Data

• Displays sensor readings with gauge, level, and text indicators for temperature, light intensity, and distance respectively.
• Line charts depict sensor readings over time.
• Includes Skymind logo and real-time clock.

Real-Time Object Detection

• Utilizes p5.js for object detection visualization.
• Embeds the object detection webpage within an iframe for seamless integration.

Enhanced with detailed installation instructions and clear delineation of features, this project aims to facilitate seamless integration of sensors and AI on Raspberry Pi, providing a comprehensive dashboard for data visualization and analysis.