IoT FitBand: Smart Health Monitoring System Using Raspberry Pi

Overview

The IoT FitBand is a smart health monitoring system designed to continuously measure and record a user’s vital health parameters including heart rate, body temperature, and humidity. The system uses a Raspberry Pi 4 Model B as the main processing unit and integrates a Pulse Sensor, DHT11 sensor, ADS1115 Analog-to-Digital Converter, OLED display, and buzzer.

Measured values are displayed on an SSD1306 OLED screen for local monitoring and uploaded to the ThingSpeak cloud for remote visualization and analysis. The buzzer activates automatically whenever readings exceed predefined thresholds.

This project demonstrates the application of Internet of Things (IoT) technology in healthcare, enabling continuous, low-cost, and accessible health monitoring.

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Features

• Real-time monitoring of heart rate, temperature, and humidity
• OLED display for local visualization
• Cloud integration via ThingSpeak
• Buzzer alerts for abnormal readings
• Low-cost, reliable, and scalable system

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System Architecture

Circuit Diagram

The circuit integrates multiple sensors connected via GPIO and I2C interfaces to the Raspberry Pi. The layout below shows the connections between all hardware components.

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Hardware Components

Component	Description	Function
Raspberry Pi 4 Model B	Main controller with Wi-Fi capability	Handles data acquisition and cloud communication
DHT11 Sensor	Digital temperature and humidity sensor	Measures temperature and humidity
Pulse Sensor	Analog heart rate sensor	Detects heartbeat and sends analog signal
ADS1115 ADC	16-bit Analog-to-Digital Converter	Converts analog pulse data to digital form
SSD1306 OLED Display (0.96")	I2C display module	Displays real-time readings
Buzzer Module	Active 3.3V buzzer	Alerts on threshold exceedance
Breadboard and Jumper Wires	—	Circuit connections

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Software Components

Software	Purpose
Raspberry Pi OS (Debian/Linux)	Operating system
Python 3	Programming language
Adafruit CircuitPython Libraries	Sensor and display interfacing
ThingSpeak Cloud	IoT data storage and visualization
VNC / SSH / Thonny IDE	Coding and debugging

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Circuit Connections

Module	Raspberry Pi Pin	Description
DHT11 Sensor	GPIO4 (Pin 7)	Data signal
ADS1115 (I2C)	SDA → GPIO2 (Pin 3), SCL → GPIO3 (Pin 5)	I2C communication
Pulse Sensor	A0 input on ADS1115	Heartbeat signal
OLED Display (SSD1306)	SDA → GPIO2, SCL → GPIO3	I2C communication
Buzzer	GPIO17 (Pin 11)	Alert output
Power	3.3V and GND	Common supply and ground

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Working Principle

1. The Pulse Sensor captures heartbeat pulses as analog voltage signals.
2. The ADS1115 ADC converts these analog signals into digital values.
3. The DHT11 Sensor measures temperature and humidity.
4. The Raspberry Pi processes all sensor readings and displays them on the OLED screen.
5. Data is transmitted to the ThingSpeak IoT Cloud for real-time visualization.
6. The Buzzer activates if readings exceed preset safety thresholds.

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System Prototype

The working prototype of the IoT FitBand integrates all sensors and display modules on a breadboard. It is compact, power-efficient, and easily scalable.

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ThingSpeak Cloud Dashboard

Data from the sensors is uploaded to ThingSpeak every 20 seconds for remote monitoring. The cloud dashboard provides live graphs for temperature, humidity, and heart rate.

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Algorithm

1. Initialize GPIO and I2C interfaces.
2. Read temperature and humidity from the DHT11 sensor.
3. Read heart rate signal via ADS1115.
4. Calculate beats per minute (BPM).
5. Display values on OLED.
6. Trigger buzzer if readings exceed thresholds.
7. Upload data to ThingSpeak via HTTP API.
8. Repeat at fixed intervals.

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ThingSpeak Setup

1. Create an account at ThingSpeak.

2. Create a new channel named IoT FitBand Monitoring System.

3. Add three fields:

   • Field 1: Temperature (°C)
   • Field 2: Humidity (%)
   • Field 3: Heart Rate (BPM)

4. Copy your Write API Key and insert it into your Python script.

5. Run the program to start uploading live data.

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Installation and Setup

Step 1: Update System

sudo apt update
sudo apt install python3-pip python3-dev libgpiod2 i2c-tools -y

Step 2: Create and Activate Virtual Environment

python3 -m venv venv
source venv/bin/activate

Step 3: Install Required Libraries

pip install adafruit-circuitpython-dht
pip install adafruit-circuitpython-ads1x15
pip install adafruit-circuitpython-ssd1306
pip install Adafruit-Blinka
pip install requests
pip install pillow
pip install RPI.GPIO

Step 4: Run the Project

python3 fitband.py

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Output

OLED Display Output

IoT FitBand
Temp: 28.5°C
Hum: 52%
Pulse: 78 BPM

ThingSpeak Dashboard

• Field 1: Temperature graph
• Field 2: Humidity graph
• Field 3: Heart Rate graph

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Applications

• Real-time fitness and health monitoring
• Remote patient supervision
• Elderly care systems
• IoT-based wearable medical devices

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Future Enhancements

• Integration of additional sensors such as SpO₂ and ECG
• Development of a mobile application for live data viewing
• Machine learning-based abnormality prediction
• GPS integration for location-aware health tracking

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Conclusion

The IoT FitBand provides a complete, IoT-based real-time health monitoring solution capable of tracking vital signs and environmental conditions. Through local display and cloud connectivity, it enables continuous observation, alerts, and long-term data storage. This project demonstrates how IoT can revolutionize healthcare by providing cost-effective, accessible, and data-driven solutions for personal and remote monitoring.

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