Developing smart buildings to reduce indoor risks for safety and health of the elderly : a systematic and bibliometric analysis

Abstract

As aging problem gets severe, more elderly people require better residences to support their later lives. Considering complicated safety and health risks the elderly would encounter indoors, such as falls and sudden diseases, researchers have tried to implement smart buildings to reduce indoor risks for the elderly. Fortunately, residential buildings have benefited from rapid development of smart techniques. It is meaningful to look back on how smart buildings deal with indoor risks of the elderly. This article adopts approaches of systematic literature review to identify 92 eligible articles which proposed smart buildings for the elderly. Then the time trend, publication journals, co-authorship and co-occurrence of these eligible articles are revealed by the bibliometric analysis. Five critical targets of these smart building solutions are summarized, including fall detection, activity recognition, disease prediction, health monitoring, and emotional care. Previous smart buildings mostly adopted Support Vector Machine (SVM), classifier comparison, neural network, Hidden Markov Model (HMM) and robotics as main smart techniques. Furthermore, these different smart building techniques are generally developed for different sub-targets or integrated for one main target, that are regarded as two correlation modes between techniques and targets. Current challenges and future direction of the development of smart buildings are pointed out. This review helps to know what kinds of indoor risks of the elderly were focused by smart buildings and which smart techniques were widely applied to develop smart buildings, then provides suggestions for future research to promote smart buildings to be more safe and healthy for the elderly.