An IoT-based Context-Aware Recommender System to Improve the Quality of Life of Elderly People

In recent years, there has been a surge of interest in the use of mobile phones and the Internet of Medical Things in automated diagnosis and health monitoring. These applications play a crucial role in providing smart medical services in modern healthcare systems. The goal of this study is to create a framework that uses the Internet of Medical Things to improve the quality of life for the elderly. Using wearable sensor devices and activity recognition techniques, this study proposes a conceptual framework for a context-aware recommendation system. Using the data from the elderly, the system will track, monitor, and make recommendations based on their activity levels. Doctors can use this information to analyze the elders' daily habits and make recommendations based on them. As a result, by reducing the need for personal care, the cost of healthcare and the burden on caregivers can be reduced. The proposed framework also includes a monitoring service for elders to monitor and control their habits, which can ultimately prevent chronic diseases.