ABSTRACT:
This project presents a smart wheelchair controller using NodeMCU and the Blynk app for real-time monitoring of vital health parameters, including temperature, pulse rate, and accelerometer data for fall detection. The system integrates multiple sensors to enhance patient safety and mobility. A temperature sensor tracks body heat, a pulse sensor measures heart rate, and an accelerometer detects sudden movements or falls, triggering alerts. Data is transmitted wirelessly to the Blynk app, allowing caregivers and healthcare professionals to monitor the user's condition remotely. This IoT-based solution aims to improve patient care, ensuring prompt responses to emergencies and enhancing the overall quality of life for individuals with mobility impairments.
INTRODUCTION:
Mobility assistance and health monitoring are critical for individuals with disabilities, elderly individuals, and patients recovering from injuries. A smart wheelchair system can significantly improve their safety and quality of life by integrating IoT-based monitoring and control features. This project focuses on developing a wheelchair controller using NodeMCU and the Blynk app to monitor key health parameters such as temperature, pulse rate, and accelerometer data for fall detection.
The system consists of temperature and pulse sensors to track the user’s vital signs and an accelerometer to detect sudden movements or falls. The NodeMCU microcontroller processes the sensor data and transmits it to the Blynk app via Wi-Fi, enabling remote monitoring by caregivers or healthcare professionals. If a fall is detected or if the user’s vital signs indicate an emergency, alerts can be sent immediately, ensuring timely assistance.
By integrating real-time health monitoring and fall detection, this IoT-based smart wheelchair system enhances patient safety and provides caregivers with valuable insights, ultimately improving the overall efficiency of healthcare support.


Objective:
The objective of this project is to develop a smart wheelchair using NodeMCU and the Blynk app to enhance mobility and health monitoring for users. The key goals include:
1. Real-time Health Monitoring – Measure and display body temperature and pulse rate using sensors.
2. Fall Detection System – Use an accelerometer to detect falls and send alerts to caregivers.
3. IoT-based Data Transmission – Send real-time health data to the Blynk app for remote monitoring.
4. User Safety and Quick Response – Enable instant notifications in case of abnormal readings or falls.
5. Enhancing Mobility – Provide ease of movement while ensuring continuous health tracking.

Block Diagram