An IoT-Integrated Multi-Sensor Framework for Continuous Vital Monitoring and Fall Detection

Abstract: The rapid growth of elderly populations and patients requiring continuous medical supervision has created a demand for intelligent healthcare monitoring systems. This paper presents an IoT-integrated multi-sensor framework for continuous monitoring of vital parameters and fall detection with an automated SMS alert system using Twilio cloud services. The proposed system integrates sensors such as heart rate, SpO₂, temperature, and an accelerometer to continuously monitor the patient’s physiological condition and detect sudden fall events. Sensor data is processed using a microcontroller and transmitted through Wi-Fi to a cloud platform for real-time monitoring. When abnormal vital signs or a fall is detected, the system automatically sends an SMS alert to caregivers using the Twilio messaging API. The proposed system offers a low-cost, portable, and real-time monitoring solution for elderly care and remote patient monitoring. Experimental testing demonstrates reliable sensor readings, accurate fall detection, and rapid alert delivery through SMS notifications.

Keywords: Vital signs, IoT healthcare, MAX30100, fall detection, ESP32, temperature monitoring, wearable system.