Author
Listed:
- Nur Alisa Ali
(Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK)Â Universiti Teknikal Malaysia Melaka (UTeM))
- Abd Shukur Jaafar
(Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK)Â Universiti Teknikal Malaysia Melaka (UTeM))
- Najmiah Radiah Mohamad
(Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK)Â Universiti Teknikal Malaysia Melaka (UTeM))
Abstract
Falls remain one of the most significant health risks for the elderly, often resulting in physical injuries, psychological trauma, and increased healthcare costs. This research introduces an IoT-enabled wearable safety band that leverages ESP32 microcontrollers, an MPU6050 motion sensor, and a NEO-6M GPS module to provide real-time fall detection and emergency alerts. Unlike conventional systems that rely on costly infrastructure, the proposed device is lightweight, affordable, and user-friendly. Once a fall is detected, the system immediately transmits notifications, including GPS coordinates, to caregivers via the WhatsApp messaging API. Audible and visual alerts from an onboard buzzer and LED further enhance user safety. Controlled testing demonstrated a detection accuracy of 95%, with a minimal false positive rate. This work highlights the potential of scalable, low-cost wearable solutions to improve elderly independence and reduce emergency response times.
Suggested Citation
Nur Alisa Ali & Abd Shukur Jaafar & Najmiah Radiah Mohamad, 2025.
"ESP32-Based Iot Framework for Fall Detection and Caregiver Notification,"
International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(9), pages 9175-9182, September.
Handle:
RePEc:bcp:journl:v:9:y:2025:issue-9:p:9175-9182
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