• Mr. Ajay Raundale
• Dr. Kailash Aseri

This research is based on the enhancement of the medical services by means of the advance intelligence computer software and new base of programming platform. Let discuss about the idea and brief behind the research interest. The global population is the big tremendous growing factor in the world, though we can't say the growth of population is not good or dangerous for the humanity because every people have its own life of right and we can't avoid it. Besides that the improvement in medical science in last 50 years overall the world is very vast. With the medical instruments and pharmacy drugs advancement we are surely saves the life of people even in very dangerous case near about 89-90% accuracy and this is the most reason for the elderly population is growing on because of improvement in medical facilities but still after the age of 60-65 years the naturally human body start the not responding as compared to the age group like 30-50years peoples. Hence at the old age of senior citizen, there is most of deaths occurs by falling the person because old age for the internal reason whatever it may be. According lot of reputed studies this reason are common for the elderly death rather than natural deaths. The senior person who lives lonely or the time when they are lonely then there is no one can taking care if fall occurs of the person like in place toilet ,latrine, at night when get up for drinking water, even in ICUs etc. .So I am interested accordingly to design the system which can robustly find the falling situation of person and get alarm or any alert signal to respective care person so that we can save the life of the elder person if injury is life threatening, even if the injury due to fall is not life threatening but there is always risk of fractures and internal injury. The overall research in on the basis of above health condition so that we can get an advance boost for medical system.

Fall; action, Machine Learning; visual , Public health ,human fall-in-progress; real-time detection; fall prevention; machine learning; classification; ensemble-in-time; inflatable body airbag, Deep learning.

"Design And Development Of Intensive Eldercare Fall Alert Framework (IEFA) Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.359-366, January-2019, Available :http://www.jetir.org/papers/JETIR1901G51.pdf

"Design And Development Of Intensive Eldercare Fall Alert Framework (IEFA) Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp359-366, January-2019, Available at : http://www.jetir.org/papers/JETIR1901G51.pdf