JMIR Publications

ABSTRACT

Background:

The Internet of Things (IoT) has become more integrated into everyday life, with devices becoming permanent fixtures in many homes. As countries face increasingly older populations, the use of IoT devices to support independent living for elderly individuals and others who need support is now possible. These groups may require assistance or varying levels of monitoring within the home. Smart home technologies that are unobtrusive, continuous, and reliably monitor healthy behaviour can fill this gap. The rationale of this scoping review is to provide insight into this evolving field of research by surveying the technologies available for in-home monitoring.

Objective:

This scoping review evaluated smart home technology approaches to identify behavioural patterns and health indicators that could support caregivers and healthcare providers with standardized guidelines.

Methods:

The study used the methodological framework proposed by Arksey and O'Malley. We analyzed articles published between 2008 and 2021 to understand better the scope of smart home data used to monitor vulnerable populations. Interest in smart home research increased rapidly after 2008, as technologies became more widely available. Only journal articles in English were included from PubMed, Scopus, ScienceDirect, and CINAHL databases. Search terms included smart home, ambient assisted living, health, and monitor.

Results:

Forty-nine of the most recent and relevant articles were included in this scoping review. Most of the studies were from Europe and North America. The largest proportion of the studies were proof of concept, pilot studies, and related to the development of infrastructure architecture and testing of algorithms. Findings from these studies have been summarised by human-centric and techno-centric features. Nearly 78% of the studies have data from humans, 63 % mentioned age, and only 33 % mentioned the sex of the participants. Most of the studies had data from the elderly population (primarily female subjects) in the home setting. Nearly 60 % of the studies reported on the health status of the participants. Technocentric features included the type of data collected, the type of sensors used and analysis methods, respectively. A wide range of sensors were used across the studies, as were the variety of outcomes measured by each representing different health indicators. PIR sensors were the frequently used sensors, while activity or motion detection and recognition were the commonly used health parameters. There were many technical challenges and barriers, including a lack of collaboration and use of interdisciplinary approaches. There is no standardized definition of a smart home in the literature, and, thus, the authors proposed a new definition.

Conclusions:

In conclusion, smart home technology has the potential to improve the monitoring of vulnerable populations, especially those ageing in the community, but it has not been fully explored. The use of Big Data, artificial intelligence algorithms, including machine and deep learning, with near-real-time dissemination of the results, will be the future of in-home health monitoring.