• Ajay Raundale

With the development of new technology there are very new search research were done all over the world , in this paper I am discussing for the old age medical condition people that how we can help them with the modern technology .From few last years with the introduction of advance technology in the health care sector there is lot of eldercare systems are invent. is paper is summaries various human activities and action of old age people which can leads to danger for the patient life . This article discusses visual machine learning models designed to detect human falls accidently using by python algorithm methods. These patterns develop by aim to differentiate falls from activities of daily living (ADL) such as walking, standing, moving, lying down, sitting, and bending over. This article aims to analyze the performance of these machine learning algorithms for human fall detection. The goal of the project is to use this system in public health, such as intensive care units, hospitals, and metal shelters. e. In real time, the system advises and warns people in the vicinity of the elderly through alarm clocks and other notification methods. Various machine learning algorithms were tested on the train data set, and the best algorithm was used to train the visual data. The model was then compared to a standard behavioral database, compared to unknown real-time visual data, and predicted human conditions.

DESIGN AND DEVELOPMENT OF ELDERCARE SELF ACCIDENT DETECTION SYSTEM BY MACHINE LEARNING

"DESIGN AND DEVELOPMENT OF ELDERCARE SELF ACCIDENT DETECTION SYSTEM BY MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 1, page no.827-832, January-2021, Available :http://www.jetir.org/papers/JETIR2101319.pdf

"DESIGN AND DEVELOPMENT OF ELDERCARE SELF ACCIDENT DETECTION SYSTEM BY MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 1, page no. pp827-832, January-2021, Available at : http://www.jetir.org/papers/JETIR2101319.pdf