Vision-Based Fallen Identification and Hazardous Access Warning System of Elderly People to Improve Well-Being
W. S. L. Abeyrathne, B. G. D. A. Madushanka, H.D.N.S. Priyankara · Zenodo (CERN European Organization for Nuclear Research) · 2020
In recent years, fall recognition, and access limitation has been a challenging issue for elders and patients. The critical attribute of this research is to support the healthcare system and hence the growth in the elderly population. The need for fall warning equipment and sensors has also risen as populations have grown because it improves the lives of elderly caregivers and patients. This paper reveals a different form of detection of fall and newly discovered region, restriction of entry to mitigate the injuries that might occur. They are attempting to classify the different forms of falls that are deemed harmful. And try solutions to detect crashes utilizing tracking sensors, Ambience sensors and Sight related apps. Within this paper, it was addressed the fall identification approaches utilizing vision-based program and access limitation by first utilizing vision and then restricting by alarms and lights.