According to the Department of Health data, falls, sprains, and collisions are the leading causes of injuries in all types of incidents and household accidents. These issues are particularly pronounced among the elderly and disabled population. Our objective is to provide an accurate, convenient, and cost-effective solution to minimize the occurrence and severity of such accidents, ensuring prompt assistance and safeguarding the well-being of those affected. Furthermore, we aim to identify commercial prospects for our invention, expanding its reach to benefit individuals across various socio-economic strata. To address these objectives, we have developed Motion Guardian, a system that leverages visual machine-learning technology known as Mediapipe for motion detection. Employing the KNN algorithm and incorporating a false alarm prevention mechanism, our solution offers users a combination of precision, convenience, and stability. The versatility of our system allows for easy installation on cameras and mobile devices, with low implementation costs, presenting substantial business opportunities in future-oriented establishments such as senior centers and healthcare facilities.
