Sleepwalking Detection and Prevention System using IoT

Sleepwalking is a parasomnia disorder that can lead to hazardous situations, including falls, wandering, and injuries. This study presents a novel Internet of Things (IoT)-based wearable system designed to detect and prevent sleepwalking incidents in real time. The system consists of a wearable device that continuously monitors movement using a pedometer sensor and a caregiver monitoring unit for remote alerts. An ESP32 microcontroller processes motion data, activates a mild electrical stimulus through a shock module to awaken the user, and transmits alerts via Bluetooth to notify caregivers. The system follows a threshold-based detection algorithm to identify sleepwalking behavior and trigger timely intervention. Experimental evaluations demonstrate the system’s reliability, low computational cost, and real-time responsiveness. However, practical limitations such as false positives, user discomfort, and Bluetooth range constraints must be addressed for broader adoption. Overall, the proposed system provides an efficient, real-time, and low-power solution for sleepwalking prevention, enhancing both user safety and caregiver awareness.