## 6 Conclusions  
This article reviewed the AISH literature, including key findings of smart home efforts, over the last decade. A systematic thorough review was conducted, including a bibliographic analysis of 160 papers and a content analysis of 87 chosen papers. Details of the selected papers are presented in tables and figures, which can be useful for scholars to readily identify the gaps in the literature and develop directions for further investigations. The article comprehensively reviewed the viability of the innovative idea of developing smart home systems with the integration of EMSs and personal care systems, which are fairly adopted in various locations. The article carefully investigated the AISH dataset on literature and divided it into three main groups for detailed analysis. The first group of papers mainly discussed the utilization of IoT in smart homes and focused on the usefulness of the systems. The usefulness concept is a key factor of the innovation process as mentioned and needs to be assessed in system development. The second group referred to energy efficiency in different contexts and peak power saving, network energy consumption, and network utility cost. The papers of this group focus on network development and measuring energy consumptions. The third group of the AISH dataset covered more topics and were divided into three themes for conducting detailed content analysis: (a) energy management in smart homes, presenting the current smart home practices in terms of energy consumption monitoring, and energy efficiency; (b) applications of AI in smart homes, such as machine learning and deep learning algorithms applied in different contexts; and (c) aged-care systems, which are adopted in different locations and can be learned from these practices. Both quantitative analysis and the comprehensive content review results showed the state-of-the-art technology used in the smart home development studies and practices and the most applications of those technologies for energy efficiency and aged occupants. This review article also showed how fragmented the literature of smart home is in terms of using different technologies for system architecture and smart system development. This extensive critical review based on a systematic approach showed that there is a large gap in the literature since a portion of it is focused on energy efficiency and aged care system development. The findings also identified a considerable gap in terms of AI/IoT integration with geospatial data. However, there is a lack of understanding about occupants' habits and contextual requirements, which would need to be considered in AI algorithms in helping occupants to save time, cost, and energy. The AISH failed to provide a comprehensive system linking different spaces, such as parking, surrounding area, kitchen, bedrooms, and all appliances and security devices. Furthermore, the data needs to be linked to building information modeling (BIM) to provide clear monitoring and warning systems about maintenance while considering the occupant usages overtime. This article, based on experimentation reports and thoughts on the current practices and published research, provided helpful starting points for future studies on smart home improvements for energy efficiency and quality of life. This review might help designers since it presents the state-of-the-art and reveals contradictories or any inconsistencies in the smart home literature. This article might also be crucial for scholars and practitioners who aim to design a road map for developing future smart homes before 2030. Conceptualization, and methodology: S.S. and S.S. ([PERSON]); writing, review, and editing, all co-authors: S.S., R.K., L.F., F.M., S.S. ([PERSON]), S.M.E., F.H., L.A.; visualization, S.S., R.K., S.M.E. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest.