International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
A FALL DETECTION SMART WATCH USING IOT AND DEEP LEARNING Abhijith V¹,Amruthkosh V Nair¹, Gopikrishnan V R¹, Nadeem S¹, Sivakumar R² ¹UG Scholar, Department of Computer Science and Engineering ²Asst.Prof, Department of Computer Science and Engineering UKF College of Engineering and Technology, Kollam, Kerala -----------------------------------------------------------------***------------------------------------------------------------------ABSTRACT (IoT) are the main techniques that have been developed to gather various information data for different services and application. Monitoring of elderly and disabled people is very challenging and due to accident which may occur due to some activities like falls. In smart homes fall is considered as the main reason for death of post traumatic complication by using artificial intelligence(AI),Internetofthings,wearables,smartphones etc.we can avoid this issues.this will helps the survival rate of the person who needs help.This leads to a suitable design fall detection system for smart homecare.In this paper we are trying to implement an IoT enabled elderely fall detection model using optimal deep convolutional nuero network for smart homecare(IMEFD-ODCNN) for smart home care.The main aim of the IMEFD-OCDNN model is to enable smartphones and intelligent deep learning algorithms to detect the event of falls in the smarthomes.Falling is among the foremost damaging event elderly people may experience. With the ever-growing aging population, there's an urgent need for the event of fall detection systems. due to the rapid development of sensor networks and also the Internet of Things (IoT), human-computer interaction using sensor fusion has been considered a good method to handle the matter of fall detection INTRODUCTION In recent years, the net of Things (IoT) and mobile communication find useful in healthcare sector. With an enhanced healthcare system in several countries, average life has developed considerably. Plus lower natural increases lead to an elderly population that will need appropriate care and more interest. But, in several countries, offering appropriate care may well be challenging due to several reasons. The impaired and elderly populations would shortly sleep in smart homes [1], [2]. These homes offer a pleasing and safe place for the elders. Independently, security is considering the most concern within the smart healthcare model [3]. However, daily emergency incidents also will still occur because of seniors’ attribute. Falling is that the commonest problem encountered by elder peoples. For elder adults, a fall might be highly risky and might cause serious health issues. Additionally, lack of balance and fall could be symptoms of a life-threatening disease. Nevertheless of the cause for a fall, it may be critical if it happens, the injured people must obtain quick help. Frequently, the individual won't be ready to get up with no support and might require immediate medical consideration. over nine percent of the population of China was aged 65 or older in 2015 and within 20 years (2017–2037) it's expected to achieve 20%1. in line with the globe Health Organization (WHO), around 646 k fatal falls occur every year within the world, the bulk of whom are suffered by adults older than 65 years (WHO, 2018),followed by road traffic injuries. Globally, falls are a significant public pathological state for the elderly. Needless to mention, the injuries caused by falls that elderly people experience have many consequences to their families, but also to the healthcare systems and to the society at large. As illustrated in Figure 1, Google Trends2 show that fall detection has drawn increasing attention from both academia and industry, especially within the last few years, where a increment are often observed. Moreover, on the identical line, the subject of fall-likelihood prediction is extremely significant too, which is not to mention some applications focused on prevention and protection.
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