

Elderly Care And Social Interaction
Abstract
online platforms are essential to social interaction and information exchange in today's digital age. However, elderly people, especially those who live alone face serious obstacles, thus this it is an urgent topic requiring quick intervention. The main problem is isolation because a lot of older people do not have the digital literacy or access to engage in online social interactions. This leads to feelings of loneliness. Health monitoring is essential since autonomous older people frequently lack access to timely healthcare supervision, which can result in health conditions going unnoticed and delayed medical action. In addition, crises can become life-threatening, and older people who live alone may find it difficult to call for help in the event of an accident or medical emergency. In response to these challenges, our project introduces an Elderly Care and Social Interaction platform. This system allows for virtual social interactions with loved ones and proactively examines living circumstances and health. Our initiative seeks to greatly improve the quality of life for independent older people by combining technology and compassion. This will ensure their well-being in a society driven by digital technology, where social connection and health monitoring are crucial. In this model we aim to simulate data representing health metrics (heart rate, temperature) and environmental data (motion events) to create real time monitoring and implement an alert system that send real time alerts to caregivers in situations of emergency. We also intend to create a software-based platform where users can virtually interact through voice call aided by hand gesture recognition and chat functionalities. Through this project, we intend to create a wholesome and user-friendly online platform for the elderly community that can help them to live their life to the fullest.
References
Shuai Shao, Jinsoek Woo, Kouhei Yamamoto, Naoyuki Kubota. “Elderly Health Care System Based On High Pecision Vibration Sensor.”, 2019 International Conference On Machine Learning and Cybernetics(ICMLC),Kobe, Japan.
Mubarak Almutairi, Lubna A.Gabralla, Saidu Abubakar, Haruna Chiroma, “Detecting Elderly Behaviours Based on Deep Learning for Healthcare: Recent Advances, Methods, Real-World Applications and Challenges”, IEEE Access(Volume:10).
Yue Geng, Chenlu Jia, Shuo Sun. “Research on Intelligent elderly care system based on Neural Network” 2022 International Conference on Big Data, Information and Computer Network (BDICN). Shenyang Institute of science and technology, Shenyang, 110000, China.
Toru. Kobayashi, Kazushige. Katsuragi. “Social Media Mediation System for Elderly People” 2016 IEEE International Conference on Consumer Electronics (ICCE), Graduate School of Engineering, Nagasaki University, Nagasaki, Japan.
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