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Project -142 IOT based IV BAG monitoring system

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Project -142 IOT based IV BAG monitoring system
This project presents the design and implementation of a Health Monitoring System utilizing an ESP-8266 microcontroller to gather real-time data from various sensors for continuous health tracking. The system integrates multiple sensors including a Load Cell Sensor for measuring body weight, the MAX30102 Pulse Oximeter and Heart Rate Sensor for monitoring oxygen levels and heart rate, a DHT11 Humidity Sensor to measure environmental humidity, and the DS18B20 Waterproof Digital Temperature Sensor to track body temperature. Additionally, a Pulse Sensor measures heartbeats directly. For alerts, a 12V Buzzer is used to notify the user of any abnormal health readings. This compact system offers a low-cost, efficient, and real-time solution for monitoring key health parameters, suitable for both personal health tracking and clinical applications.
Wireless data transmission and cloud integration are also possible through the ESP-8266, enabling remote monitoring and analysis of patient data.
This project presents the design and implementation of a Health Monitoring System utilizing an ESP-8266 microcontroller to gather real-time data from various sensors for continuous health tracking. The system integrates multiple sensors including a Load Cell Sensor for measuring body weight, the MAX30102 Pulse Oximeter and Heart Rate Sensor for monitoring oxygen levels and heart rate, a DHT11 Humidity Sensor to measure environmental humidity, and the DS18B20 Waterproof Digital Temperature Sensor to track body temperature. Additionally, a Pulse Sensor measures heartbeats directly. For alerts, a 12V Buzzer is used to notify the user of any abnormal health readings. This compact system offers a low-cost, efficient, and real-time solution for monitoring key health parameters, suitable for both personal health tracking and clinical applications.
Wireless data transmission and cloud integration are also possible through the ESP-8266, enabling remote monitoring and analysis of patient data.