ABSTRACT
At this moment of the COVID-19 epidemic, it is difficult for caregivers to be fully aware of the elderly by closing care to prevent accidents at home. Existing research, home-based self-health management strategies, by using contextual tools and a lack of empirical procedures or technological components in internet monitoring, home accidents from individualized patterns has not been achieved. We use vision detecting through the internet monitoring method in a smart lighting materials house to fill this research gap. We examined the impact of physical transitions and visibility on fall detection and compared the accuracies of fall prediction based on combinations of related factors. The results indicated that including both physical transitions and visibility would enable older people to avoid falls. We evaluated the impact of physical transitions and visibility on fall detection and compared the accuracy of falls based on combinations of related factors. The accuracy of predictions using both physical transition and visibility was higher than 81%, which is a high forecasting accuracy rate. Those are significant contributions to the elderly in applied economics.