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Biophilic design is a well-recognised discipline aimed at enhancing health and well-being, however, most buildings lack adequate representation of nature or nature-inspired art. Notable barriers exist such as wealth, education, and physical ability restricting people’s accessibility to nature and associated artworks. An AI-based Biophilic arts curation and personalised recommendation system were developed in this study to improve accessibility to biophilic arts. Existing Biophilic research mainly focuses on building design principles, limited research exists to examine biophilic arts and associated emotional responses. In this paper, an interdisciplinary study addresses this gap by developing metrics for Biophilic art attributes and potential emotional responses, drawing on existing Biophilic architecture attributes and PANAS items. A public survey of 200 participants was developed in this study. The survey collected art viewers’ ratings of Biophilic attributes and associated emotional responses to establish statistical correlations between Biophilic attributes and emotional responses. The statistical analysis established a positive correlation between Biophilic attributes and positive emotions. The public survey results show significant positive emotional impacts (p-value <0.05) after exposure to Biophilic images, supporting further research and development of the Biophilic art curation system. This digital curation system employs Computer Vision algorithms (ResNet50) to automate Biophilic art categorisation and generate personalised recommendations. This study emphasises the importance of integrating nature into built environments. It proposes that artificial intelligence could significantly enhance the categorisation and recommendation of Biophilic art, advocating for expanding Biophilic art databases for emotionally responsive art display systems, benefiting mental health, and making art more accessible.

The spatial layout of urban villages seriously affects the living environment and integrated development of urban and rural areas. Using digital means to assist in the reconstruction of urban villages is necessary and urgent. This study built an urban renewal framework for intelligent building planning with a proposed multi-party collaborative pattern. First, villagers’ needs, and relevant standards and regulations were merged into planning requirements, which were formulated into planning goals and criteria. With the quantitative goals and criteria, building planning and design algorithms were developed. Furthermore, the method was verified to achieve an intelligent layout of buildings. Finally, under certain conditions, the average difference between the plot ratio calculated by the program and the actual plot ratio was 0.02, and that between the building intensity calculated by the program and the actual building intensity was 0.02. Within 11.43 hectares, 500 buildings were generated with a total floor area of 27.72 hectares, and the average time taken for scheme generation was 10 s. This method can efficiently generate a plan similar to the actual floor area ratio and building density and optimize the problem of insufficient spacing. Moreover, adjusting the parameters can automatically generate a variety of schemes that can support the layout design of rural buildings.

The feasibility of achieving sustainable building development, an eco-friendly environment, and building investment conservation by integrating technological intelligence in buildings is highly viable. Intelligence features are, therefore, increasingly being incorporated in new designs and existing buildings to enhance the useful life, productivity and satisfaction of occupants, and a greener environment. This article evaluates the use of intelligent building systems in Nigeria. Primary data were obtained with the use of structured questionnaires that were self-administered to construction professionals in the private and public sectors in Lagos State. Data collected were analysed using descriptive and inferential statistics. Findings established that 90.24% of the respondents were aware of intelligent building systems, while practitioners who have worked or were working on buildings with intelligent features were limited to 51.2%. Approximately 64.60% of the respondents have used intelligent buildings previously, but only thirteen (13) notable buildings were identified to have employed intelligent building systems to a reasonable extent in the study area. The features of intelligent buildings with top level of awareness were CCTV system; access control and locks (mean = 3.96); alarms and alerts (mean = 3.92); HVAC system (mean = 3.90), and fire alarm system (mean = 3.89). Features with high level of utilisation include lighting system, which was the most utilised feature (mean = 3.57); fire alarm system (mean = 3.48); access control and lock; CCTV system (mean = 3.45), and HVAC system (mean = 3.43). The results showed that most of the features with a high level of awareness were also those with a high level of utilisation. The study established that the level of awareness and utilisation of intelligent building systems in the study area is high, but full adoption of the system is still low.  

Since 1985, various intelligent technologies have introduced and policy-driven in Taiwan, the intelligent building system has gradually formed catering for the characteristics of Taiwan. Therefore, this study proceeds to explore current status and survey strategies of policy implementation for intelligent buildings development in Taiwan, and further obtained countermeasures for building developers and public sectors in implementation intelligent buildings. The study firstly proceeds to relevant literature review and analysis of intelligent buildings both domestic and foreign, and through statistic and analysis in case studies and content analysis method, acquires Taiwan intelligent building evaluation indicator items for normal and non-normal application of intelligent building system by building developers and public sectors. Through study found four evaluation indicator items of normal application, and one evaluation indicator items of non-normal application, as well as building developers selected quantity and items of evaluation indicator fewer than public sectors. It is expected that study result will providing assessment and references to building developers and public sectors for the direction and implement strategy of intelligent building development in future, and further promote the realization goal of sustainable intelligent green building in Taiwan.

The networks of intelligent building are usually consist of a great number of smart devices. Since many smart devices only support on-site configuration and upgrade, and communication between devices could be observed and even altered by attackers, efficiency and security are two key concerns in maintaining and managing the devices used in intelligent building networks. In this paper, the authors apply the technology of software defined networking to satisfy the requirement for efficiency in intelligent building networks. More specific, a protocol stack in smart devices that support OpenFlow is designed. In addition, the authors designed the lightweight security mechanism with two foundation protocols and a full protocol that uses the foundation protocols as example. Performance and session key establishment for the security mechanism are also discussed.

The building sector is one of the largest contributors to the world’s total energy use and greenhouse gas emissions. Advancements in building energy technologies have played a critical role in enhancing the energy sustainability of the built environment. Extensive research and new techniques in energy and environmental systems for buildings have recently emerged to address the global challenges. This study reviews existing articles in the literature, mostly since 2000, to explore technological advancement in building energy and environmental systems that can be applied to smart homes and buildings. This review study focuses on an overview of the design and implementation of energy-related smart building technologies, including energy management systems, renewable energy applications, and current advanced smart technologies for optimal function and energy-efficient performance. To review the advancement in building energy-related technologies, a systematic review process is adopted based on available published reviews and research types of articles. Review-type articles are first assessed to explore the current literature on the relevant keywords and to capture major research scopes. Research-type papers are then examined to investigate associated keywords and work scopes, including objectives, focuses, limitations, and future needs. Throughout the comprehensive literature review, this study identifies various techniques of smart home/building applications that have provided detailed solutions or guidelines in different applications to enhance the quality of people’s daily activities and the sustainability of the built environmental system. This paper shows trends in human activities and technology advancements in digital solutions with energy management systems and practical designs. Understanding the overall energy flow between a building and its environmentally connected systems is also important for future buildings and community levels. This paper assists in understanding the pathway toward future smart homes/buildings and their technologies for researchers in related research fields.

Since the 1980s, smart buildings have aroused the interest of researchers. However, there is still no consensus on what the intelligence of a building is, and what enhances that intelligence. The purpose of this paper is to identify and correlate the main drivers and systems of smart buildings, by associating them with the main beneficiaries: users, owners, and the environment. To identify the main drivers and systems of these buildings, we carried out a comprehensive, detailed, and interpretative literature search. From the selected articles, we sorted the information, extracted the main concepts and knowledge, and, finally, identified the set of potential drivers and systems. Results showed eleven drivers and eight systems, and these can be enhanced by more than one driver. By analyzing the main beneficiaries, we grouped the drivers into three categories: users, owners, and the environment. Given the lack of consensus on the key drivers that make buildings smarter, this article contributes to filling this gap by identifying them, together with the key systems. It is also relevant for detecting the relationships between drivers and systems, and pointing out which drivers have the greatest potential to affect a particular system, keeping in mind the main beneficiary.

This article describes the design and verification of the indirect method of predicting the course of CO 2 concentration (ppm) from the measured temperature variables T indoor (°C) and the relative humidity rH indoor (%) and the temperature T outdoor (°C) using the Artificial Neural Network (ANN) with the Bayesian Regulation Method (BRM) for monitoring the presence of people in the individual premises in the Intelligent Administrative Building (IAB) using the PI System SW Tool (PI-Plant Information enterprise information system). The CA (Correlation Analysis), the MSE (Root Mean Squared Error) and the DTW (Dynamic Time Warping) criteria were used to verify and classify the results obtained. Within the proposed method, the LMS adaptive filter algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, specifically from February 1 to February 28, 2015, from June 1 to June 28, 2015 and from February 8 to February 14, 2015. For the best results of the trained ANN BRM within the prediction of CO 2 , the correlation coefficient R for the proposed method was up to 92%. The verification of the proposed method confirmed the possibility to use the presence of people of the monitored IAB premises for monitoring. The designed indirect method of CO 2 prediction has potential for reducing the investment and operating costs of the IAB in relation to the reduction of the number of implemented sensors in the IAB within the process of management of operational and technical functions in the IAB. The article also describes the design and implementation of the FEIVISUAL visualization application for mobile devices, which monitors the technological processes in the IAB. This application is optimized for Android devices and is platform independent. The application requires implementation of an application server that communicates with the data server and the application developed. The data of the application developed is obtained from the data storage of the PI System via a PI Web REST API (Application Programming Integration) client.