• NIKITA PRASHANT PATIL
• PRITI ANANT CHOPADE
• PRITI MAHESH KOLTE
• AISHWARYA SUBHASH SURALKAR
• YOGESH B. JADHAO

ABSTRACT: Personalized monitoring ad its application is increasing with an advancement of technology. And during pandemic its become very essential to keep an eye on the prone area and one of the area to identify was old age home. Dizziness, unconsciousness and other are the common problems associated with elderly people due to weakness and this was also the symptoms of covid. So an unusual activity of falling of elderly people was very difficult to identify and also to monitor. The technology was updated till now to identify posture of normal activity such as running, walking, jumping and many but revert to that falling was an area need to explore. During fall of an elderly people the injuries are very fatal and to void this case a remedial solution is design to identify the fall and try to notify te system about its fall. Although we try to predict the fall so that it become easy to monitor and provide medical help as soon as possible. The main theme is to identify the posture activity and once identify we will compare the activity with trained datasets and if its normal in vision them no notification occurred and if the percentage of fall was high them we can predict the system as fall video.

Keywords—Elderly People, Activity Detection, Fall Detection, Predicted

"Human Activity Recognition And Fall Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.h228-h235, May-2022, Available :http://www.jetir.org/papers/JETIR2205830.pdf

"Human Activity Recognition And Fall Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. pph228-h235, May-2022, Available at : http://www.jetir.org/papers/JETIR2205830.pdf