A Proposed Model for Fainting People Detection Using Media Pipe Technology

Abstract

Nowadays, falls put patients' safety and health in danger in hospitals and assisted living facilities, especially at night. The camera system used in this study is the suggested model; it records video footage and, in real time, analyzes patterns using Media Pipe algorithms to detect fainting or falls. An instant alert is generated and sent to a mobile app connected to the camera system if such an event is detected. The caretakers, nurses, or security officers entrusted with providing assistance can communicate with each other using the smartphone application. They follow the message to a specific location. Lastly, the system aims to improve the quality of care and support for the senior population by accelerating the response to instances of fainting and falling through the use of computer vision technologies and real-time notifications.