A Review of Smart House Analysis Methods for Assisting Older People Living Alone

Abstract

Smart Houses are a prominent field of research referring to environments adapted to assist people in their everyday life. Older people and people with disabilities would benefit the most from the use of Smart Houses because they provide the opportunity for them to stay in their home for as long as possible. In this review, the developments achieved in the field of Smart Houses for the last 16 years are described. The concept of Smart Houses, the most used analysis methods, and current challenges in Smart Houses are presented. A brief introduction of the analysis methods is given, and their implementation is also reported.

Elderly Perception on the Internet of Things-Based Integrated Smart-Home System

“…In previous studies, various smart home sensors have been applied in smart home systems for the elderly's health-related benefits (fall detection, healthcare monitoring, and activity of daily living recognition) and environmental benefits (energy consumption and indoor air quality management) [10,11]. Falling is an accident that frequently occurs among elderly people, requiring immediate detection to reduce its adverse consequences on the health of the elderly [7].…”

“…In previous studies, various standalone smart home systems have been developed, mostly dealing with specific benefits for the elderly. The benefits include fall detection [7], healthcare monitoring [1,8], ADL recognition [48], iAQ monitoring, and energy consumption monitoring [10,11]. All these factors are essential for effectively improving the elderly's overall QoL.…”

“…To address this problem, smart home systems are receiving attention, which are residential environments equipped with Internet of Things (IoT) sensors to provide ambient assistance to the elderly [1,10]. For the development of smart home systems, in previous studies, various IoT sensors incorporating both wearable and non-wearable smart home sensors have been applied for the benefits of the elderly-care [11], which can be largely classified into health-related and environmental benefits.…”

The SmartHabits: An Intelligent Privacy-Aware Home Care Assistance System

“…Sanchez at al. [14] describe smart home developments and challenges in the last 16 years together with the most used analysis methods for human activity and behavior recognition and their implementations. They identify most implemented analysis methods in the period from 2000 to 2016, which includes the Bayesian network, Naïve Bayes/Decision Trees, Decision Trees, Computer vision, Intelligent Agents (IA), Computer vision/IA, Correlated pattern, Gaussian Distribution, Kernel Density Estimation, Mix models, Maximum likelihood, T-Patter, Hierarchical Classifiers, Quadratic Discriminatory Classifier, Principal Component Analysis/K-Nearest Neighbors, Fuzzy Logic, Fuzzy Logic/IA, IA/Bayesian Net, IA/Lezi, Lezi, Markov model/IA, Markov Model, Neural Network (NN), Markov Model/NN, NN/Support Vector Machines (SVM), SVM, and SV Data Description.…”

Application of Internet of Things in a Kitchen Fire Prevention System

“…Based on people's demand for energy saving in their homes, the development of smart house technology is an inevitable result [16][17][18][19][20]. A smart house refers to the integration of all automation equipment through the network system to provide a service that is highly efficient overall, thereby ensuring that the public's needs are met in terms of home safety, a healthy and humane living environment, convenience, and quality of life [21]. The modern smart home system includes the following subsystems: lighting, climate control, security, technical incidents prevention subsystem and others [22][23][24].…”