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.
Keywords: COVID-19, Home-based, Physical transition, Visibility, Fall
detection.