Welcome to the IoT-Based Real-Time Patient Health Monitoring System! This system uses IoT technology to continuously monitor vital health parameters such as body temperature, ECG, heart rate, and pulse rate. The collected data is then transmitted to the cloud for analysis and easy monitoring. 🏥🌐
An advanced IoT-powered system that tracks heart rate ❤️, temperature 🌡, SpO2 ⏳, and ECG in real-time. 🚨 Alerts doctors instantly in emergencies, stores data securely in the cloud ☁, and provides remote patient monitoring 📊📱. Revolutionizing healthcare with AI-driven insights! ⭐
This health monitoring system is designed to provide real-time monitoring of patients' key health metrics. Using MAX30100 (for pulse oximetry), DS18B20 (for temperature), and an ECG sensor, the system ensures continuous tracking of a patient's heart rate, oxygen saturation, body temperature, and ECG readings. Alerts are triggered if any of the values go out of the safe range. 🚑
2.1 Real-Time Data Monitoring : Track key health parameters like temperature, heart rate, SpO2, and ECG. 💓📈
2.2 Abnormal Condition Alerts : Get immediate alerts (LED/Buzzer) when any vital sign goes outside normal limits. 🚨
- MAX30100: For heart rate and SpO2 measurement.
- DS18B20: For body temperature measurement.
- ECG Sensor: For capturing ECG data.
- ESP8266: For Wi-Fi connectivity.
- LCD Display: For displaying live data.
- Arduino IDE for writing the firmware.
- Ubidots for cloud integration.
- Wire.h
- LiquidCrystal_I2C.h
- ESP8266WiFi.h
- Ubidots.h
- MAX30100_PulseOximeter.h
- DallasTemperature.h
- OneWire.h.
The system collects data from MAX30100 (heart rate, SpO2), DS18B20 (temperature), and ECG sensor.
The health metrics are continuously monitored for any abnormal readings.
If abnormal conditions are detected (e.g., high temperature, low oxygen levels, irregular heart rate), the system activates a red LED and buzzer for alerting. 🆘 If the system detects abnormal conditions like high temperature, low oxygen levels, or irregular heart rate, it activates a red LED for a visual alert and triggers a buzzer for an audible warning. This ensures immediate attention and helps in early detection of potential health risks, allowing for quick action. 🚨
Every 16 seconds, the data is sent to Ubidots for storage and further analysis.
The real-time readings are displayed on the LCD for quick checks. 🖥️
git clone https://github.com/syedmaazsaeed/IOT-Based-Real-Time-Patient-Health-Monitoring-System
5.2 Install Libraries 📚
Download and install the following libraries from the Arduino IDE Library Manager:
- LiquidCrystal_I2C
- ESP8266WiFi
- Ubidots
- MAX30100_PulseOximeter
- DallasTemperature
- OneWire
5.3 Connect Hardware 🔌
- Connect the MAX30100 sensor to your ESP8266 (pins configured in the code).
- Connect the DS18B20 sensor to the OneWire bus.
- Connect the ECG sensor to the appropriate analog pin.
- Connect the LCD for real-time display.
5.4 Upload the Code
Upload the code to your ESP8266 using the Arduino IDE.
5.5 View Data 📊
- Open the serial monitor to view the console output.
- Connect to the Ubidots dashboard to view real-time health data.
- Monitor the LCD for immediate feedback on the patient's condition. 📱
6.1. Machine Learning Integration: Use AI to analyze patterns in health data and predict potential health issues. 🤖 6.2. Mobile Application: Build a mobile app to receive real-time health data and alerts. 📲 6.3. Expand Sensor Suite: Add more detectors like ECG or pulse wave sensors for deeper health insights. 📊
Have thoughts or suggestions? Kindly get in touch via email or issues! Let's work together to innovate healthcare! 🎍🌍💡..