Published on: April 2026
AI-POWERED ELDERLY FALL DETECTION
Akshatha. R Harini. I
Dr. S. Niraimathi
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Abstract
Falls are among the most critical health hazards threatening the elderly population, frequently resulting in severe injuries, prolonged hospitalization, and diminished quality of life. This paper presents an AI-powered Elderly Fall Detection and Real-Time Health Monitoring System designed to address the limitations of conventional manual surveillance approaches. The proposed system integrates an ESP8266/ESP32 microcontroller with an MPU6050 accelerometer-gyroscope module, a DS18B20 digital temperature sensor, and a photoplethysmography-based pulse sensor to continuously monitor body motion, temperature, and heart rate. Fall detection is achieved through a machine learning classification algorithm that analyses 6-axis inertial measurement data to distinguish falls from normal daily activities such as walking, sitting, and standing. Upon detecting a fall or abnormal physiological condition, the system triggers a local buzzer alarm, displays an emergency message on a 16×2 LCD, and delivers instant SMS alerts via a SIM800L GSM module. Real-time health data is simultaneously transmitted to the Blynk IoT cloud application over Wi-Fi, enabling remote monitoring by caregivers. Experimental evaluation demonstrated high fall-detection accuracy with minimal false positives. The system offers a lowcost, compact, wearable, and reliable solution for enhancing elderly safety and facilitating timely emergency response.
How to Cite this Paper
R, A. & I, H. (2026). AI-Powered Elderly Fall Detection. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.386
R, Akshatha., and Harini. I. "AI-Powered Elderly Fall Detection." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.386.
R, Akshatha., and Harini. I. "AI-Powered Elderly Fall Detection." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.386.
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- •Published on: Apr 17 2026
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