Challenges caused by the care of the ageing population in many countries are becoming increasingly severe. However, high expenditures on healthcare services and the cost of infrastructure construction will be an unbearable burden for both the government and individuals. Due to its security, convenience, and lower prices compared with traditional medical care, smart home technology, which includes information and communication technologies (ICTs), artificial intelligence (AI), and the Internet of Things (IoT), can reduce the care burden. While smart home studies targeting older adults have increased, systematic analysis of these studies is lacking. CiteSpace enables rapid clustering and visualisation of the literature using scientific diagrams, exhibiting the results more comprehensibly. This analysis of academic research published within the last decade (from 2012 to 2023) through a scientometric approach can help to understand the historical variations, the latest technologies and emerging trends, and the research clusters that have emerged related to the study of smart homes for the elderly (SHFTE). The study results showed that recent research mainly centres on IoT for home automation and home-based healthcare, including wearable device applications and information security analysis. Research trends regarding SHFTE have focused primarily on developing and updating smart technologies based on the IoT, sensors, and related home monitoring. Therefore, greater emphasis must be placed on connecting smart homes and intelligent buildings with communities and societies, developing the potential of smart communities, and investigating the application of smart integration to the home and community in cities.

The evolution of university libraries from traditional knowledge bases to dynamic, multifunctional learning environments has attracted widespread attention in higher education research. This study, as a scientometric review, focuses on the combination of library space design and informal learning space, making up for the fragmented status of existing research and proposing specific design recommendations for university library space design from the perspective of informal learning space. The study used CiteSpace6.2r7 software to analyze 1434 articles from 1973 to 2024 in the Web of Science Core Collection. The analysis identified key research trends, keyword clusters, and thematic connections, confirming the importance of studying university library space design from the perspective of informal learning space. The review also explored how libraries should promote structured academic work and autonomous collaborative learning through space design by proposing design strategies by studying the symbiotic relationship between library space design and informal learning. This study provides a structured framework for the development of future library spaces and provides important reference information for optimizing learning environments to meet the changing needs of students and educators.

Effective natural lighting in university library reading areas significantly influences users’ visual comfort, task performance, and energy efficiency. However, existing library lighting designs often exhibit problems such as uneven illumination, excessive glare, and underutilization of natural daylight. To address these challenges, this study proposes a multi-objective optimization framework for library lighting design based on the NSGA-II algorithm. The framework targets the following three key objectives: improving illuminance uniformity, enhancing visual comfort, and reducing lighting energy consumption. The optimization process incorporates four critical visual comfort parameters—desktop illuminance, correlated color temperature, background reflectance, and screen luminance—whose weights were determined using the analytic hierarchy process (AHP) with input from domain experts. A parametric building information model (BIM) was developed in Revit, and lighting simulations were conducted in DIALux Evo to evaluate different design alternatives. Experimental validation was carried out in an actual library setting, with illuminance data collected from five representative measurement points. The results showed that after optimization, lighting uniformity improved from less than 0.1 to 0.6–0.75, glare values (UGR) remained below 22, and daylight area coverage increased by 25%. Moreover, lighting energy consumption was reduced by approximately 20%. Statistical analysis confirmed the significance of the improvements (p < 0.001). This study provides a systematic and reproducible method for optimizing natural lighting in educational spaces and offers practical guidance for energy-efficient and user-centered library design.

The lighting conditions of university libraries directly influence reading comfort, learning efficiency, and energy consumption. However, the current lighting design still faces problems such as uneven illumination distribution, severe glare, low utilization of natural light and high energy consumption. Especially in the reading area, due to insufficient lighting control, the light in some areas is too bright or too dark, which affects visual comfort and increases energy consumption. To this end, this study proposes a novel multi-objective optimization framework that effectively balances illumination uniformity, visual comfort, and energy efficiency using NSGA-II, outperforming conventional single-objective methods. The experimental results indicate that after optimization, illumination uniformity improved significantly from less than 0.1 to a stable range of 0.6–0.75, the average monthly energy consumption reduced by approximately 20%, and the natural lighting area expanded by approximately 25% (500m²). Unlike previous research that focuses solely on either energy efficiency or visual comfort, this study integrates multiple critical lighting parameters into a unified optimization framework, achieving a better balance between energy efficiency, lighting uniformity, and visual comfort.