Hybrid Smart Home based on AI and IoT with Complex Interwoven Activities for Cognitive Health Assessment and Monitoring

Abstract

Rapid population ageing in Europe and North America is altering regional demographics and placing strain on healthcare systems, which could ultimately lower service standards. When it comes to providing care at the patient’s point of perception, telemedicine can be a viable option because it allows, remote monitoring to the target for real time. Moreover, it also allows two-way communication with medical professionals. The majority of time for many people, regardless of age, health, or ability, is spent in their own homes. Therefore, sickness can be predicted and prevented before the patient notices any signs by transforming smart homes into diagnostic environments for real-time, continuous health monitoring. The World Health Organization states that it is impossible to assess health, well-being, or quality of life without tracking multiple, interrelated factors. The home can be transformed into a diagnostic place with the help of the sensing devices and technology we discuss in this work. We think about how to combine sensing devices across all four WHO categories in terms of raw and processed data, synchronization and transmission. To achieve hierarchical multi-layer data fusion, we use a bus-based scalable intelligent system to build a hybrid topology. This allows for both short-term monitoring (event detection and alerting) and long-term monitoring (prediction and prevention).