Project Description:

The IoT Sleep Quality Tracker is a smart health-monitoring system designed to track, analyze, and improve a user’s sleep patterns using IoT sensors and a web interface. It captures data like body movement, heart rate, room temperature, and light levels to determine sleep quality and provide personalized insights and suggestions.

The project combines IoT hardware, real-time monitoring, data analytics, and a user-friendly dashboard built using web technologies.

Core Objectives:

• Detect sleep duration, stages (deep, light, REM), interruptions.

• Provide visual reports and tips to improve sleep quality.

• Allow users to monitor sleep data historically and in real time.

Key Features:

 1. Smart Sleep Monitoring Device (IoT Hardware)

• Sensors used:

  • Heart Rate Sensor (e.g., MAX30100)

  • Motion Sensor (e.g., Accelerometer like MPU6050)

  • Temperature & Humidity Sensor (e.g., DHT11)

  • Light Sensor (e.g., LDR)

• Microcontroller: ESP32 / Arduino with Wi-Fi support.

 2. Real-Time Data Collection

• Collects physiological and environmental data during sleep.

• Sends data to the backend server via Wi-Fi using HTTP or MQTT.

 3. Data Processing & Sleep Scoring

• AI/ML algorithms analyze:

  • Restlessness (from motion)

  • Room comfort (temperature/light)

  • Sleep consistency and interruptions

• Calculates a daily sleep quality score.

 4. Web Dashboard

• Built with HTML, CSS, Bootstrap, JavaScript

• Displays:

  • Sleep trends (graphs, charts)

  • Quality scores (out of 100)

  • Tips for improvement

  • Daily/weekly/monthly summaries

 5. User Management System

• Login/Registration

• Personalized insights

• Track sleep habits over time

 6. Alert System

• Option to notify user (via email/SMS) if abnormal patterns are detected.

• Sleep reminder alarms.

Tech Stack:

Frontend:

• HTML, CSS, Bootstrap – responsive UI

• JavaScript – charts (Chart.js / D3.js)

Backend:

• PHP / Node.js / Java – handles API requests and data storage

• REST APIs for frontend to pull user data

Database:

• MySQL / MongoDB – stores user profiles and sleep records

IoT Microcontroller:

• ESP32 / NodeMCU (Arduino)

  • C/C++ for embedded programming

  • Sends data to cloud/server at intervals

Optional AI/ML:

• Python backend service using ML libraries

  • Sleep stage detection

  • Recommendation engine for better sleep