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Over the last few decades, energy efficiency has received increasing attention from the Architecture, Engineering, Construction and Operation (AECO) industry. Digital Twins have the potential to advance the Operation and Maintenance (O&M) phase in different application fields. With the increasing industry interest, there is a need to review the current status of research developments in Digital Twins for building energy efficiency. This paper aims to provide a comprehensive review of the applications of digital twins for building energy efficiency, analyze research trends and identify research gaps and potential future research directions. In this review, Sustainability and Energy and Buildings are among the most frequently cited sources of publications. Literature reviewed was classified into four different topics: topic 1. Optimization design; topic 2. Occupants’ comfort; topic 3. Building operation and maintenance; and topic 4. Energy consumption simulation.

Design strategies for sustainable buildings, that improve building performance and avoid extensive resource utilization, should also promote healthy indoor environments. The following paper contains a review of the couplings between (1) building design, (2) indoor environmental quality and (3) occupant behavior. The paper focuses on defining the limits of adaptation on the three aforementioned levels to ensure the energy efficiency of the whole system and healthy environments. The adaptation limits are described for measurable physical parameters and the relevant responsible human sensory systems, evaluating thermal comfort, visual comfort, indoor air quality and acoustical quality. The goal is to describe the interactions between the three levels where none is a passive participant, but rather an active agent of a wider human-built environment system. The conclusions are drawn in regard to the comfort of the occupant. The study reviews more than 300 sources, ranging from journals, books, conference proceedings, and reports complemented by a review of standards and directives.

Worldwide increasing awareness of energy sustainability issues has been the main driver in developing the concepts of (Nearly) Zero Energy Buildings, where the reduced energy consumptions are (nearly) fully covered by power locally generated by renewable sources. At the same time, recent advances in Internet of Things technologies are among the main enablers of Smart Homes and Buildings. The transition of conventional buildings into active environments that process, elaborate and react to online measured environmental quantities is being accelerated by the aspects related to COVID-19, most notably in terms of air exchange and the monitoring of the density of occupants. In this paper, we address the problem of maximizing the energy efficiency and comfort perceived by occupants, defined in terms of thermal comfort, visual comfort and air quality. The case study of the University of Pisa is considered as a practical example to show preliminary results of the aggregation of environmental data.

Without a well-defined energy management plan, achieving meaningful improvements in human lifestyle becomes challenging. Adequate energy resources are essential for development, but they are both limited and costly. In the literature, several solutions have been proposed for energy management but they either minimize energy consumption or improve the occupant’s comfort index. The energy management problem is a multi-objective problem where the user wants to reduce energy consumption while keeping the occupant’s comfort index intact. To address the multi-objective problem this paper proposed an energy control system for a green environment called PMC (Power Management and Control). The system is based on hybrid energy optimization, energy prediction, and multi-preprocessing. The combination of GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is performed to make a fusion methodology to improve the occupant comfort index (OCI) and decrease energy utilization. The proposed framework gives a better OCI when compared with its counterparts, the Ant Bee Colony Knowledge Base framework (ABCKB), GA-based prediction framework (GAP), Hybrid Prediction with Single Optimization framework (SOHP), and PSO-based power consumption framework. Compared with the existing AEO framework, the PMC gives practically the same OCI but consumes less energy. The PMC framework additionally accomplished the ideal OCI (i-e 1) when compared with the existing model, FA–GA (i-e 0.98). The PMC model consumed less energy as compared to existing models such as the ABCKB, GAP, PSO, and AEO. The PMC model consumed a little bit more energy than the SOHP but provided a better OCI. The comparative outcomes show the capability of the PMC framework to reduce energy utilization and improve the OCI. Unlike other existing methodologies except for the AEO framework, the PMC technique is additionally confirmed through a simulation by controlling the indoor environment using actuators, such as fan, light, AC, and boiler.

The paper provides a methodology for the optimal control of heating, ventilation, and air conditioning (HVAC) systems used in public buildings, with the purpose of obtaining high comfort and safety standards along with energy efficiency. The combination of the two concurrent objectives of minimizing energy use and guaranteeing high standards of occupant comfort is obtained by means of multi-objective optimization, in which a comfort model is combined along with a dynamic energy model of the building. The use of dynamic setpoints for the HVAC and the inclusion of comfort indicators represent a step forward, compared to the current design and operation procedures suggested by technical standards. The utilization of the proposed methodology is tested with reference to a case study, represented by an academic building used by the University of Pisa for educational purposes, whose extensive and variable occupancy can help to emphasize the importance of comfort in the operation of HVAC systems in different climatic conditions and with different occupancy profiles. We show how this optimization brings interesting results in terms of energy-saving (up to 30%), obtaining an increased comfort level (of more than 25%) compared to the operating conditions suggested by technical standards.

To improve buildings and their characteristics, the feedback provided directly by users is generally fundamental in order to be able to adapt the technical and structural functions to the well-being of users. The post-occupancy evaluation (POE) fits perfectly into this context. The POE, through qualitative and quantitative information on the interior environment, makes it possible to identify the differences between the performances modeled in the design phase and the real performances experienced by the occupants. This review of 234 articles, published between 2006 and 2022, aims to analyze and compare the recent literature on the application of the POE methodology. The aim was to provide both a qualitative and quantitative assessment of the main factors that comprise the indoor environmental quality (IEQ). The study highlighted the factors that comprise the quality of the indoor environment, as well as the variables that are usually analyzed to describe the well-being of the occupants. The results suggested which are the most common approaches in carrying out POE studies and will identify the factors that most influence the determination of the good quality of an indoor environment.

Manual demolition activities in urban environments can generate significant vibrations that propagate to neighboring buildings, potentially affecting occupant comfort and structural integrity, yet limited research exists on vibrations induced by hand-operated demolition tools. This study investigates the dynamic response of a three-story masonry residential building subjected to vibrations from manual demolition work using different tools (small hammer, large hammer, pneumatic hammer, and circular saw). Experimental measurements were conducted using piezoelectric accelerometers positioned across three building levels, while a three-dimensional finite element model was developed in SAP2000 and calibrated against experimental data through modal analysis. The experimental campaign identified dominant vibration frequencies between 11 and 14 Hz, corresponding to the first six structural modes of the building. An accurate Finite Element Model is calibrated on the experimental results. The validated numerical procedure, calibrated through experimental modal data, enables the assessment of vibration levels induced by manual demolition activities and facilitates parametric studies for different scenarios, providing a practical tool for structural engineers.

Occupant comfort in buildings is one of the most crucial considerations in designing a building. Accordingly, there is a growing interest in this area. Aspects of comfort include thermal comfort, visual comfort, acoustic comfort, and indoor air quality (IAQ) satisfaction. The objective of this state-of-the-art review was to provide a comprehensive, explicit, and up-to-date literature review on occupant comfort in buildings, since this issue has a great impact on the lifestyle, health, and productivity of occupants. A meta-synthesis method was also used for an analytical-interpretive review of previous studies. In this research, scientific research studies related to the subject of indoor occupant comfort in the period 2002–2022 were reviewed. Previous reviews have often covered the fundamental concepts and principles related to indoor occupant comfort. Although innumerable studies have focused on thermal comfort, other aspects of occupant comfort have not been considered. The review is analyzed and discussed in reference to type of study, case study geographical locations and climate zones, case study building types, decision-making models, assessment criteria, data-collection tools, and data analysis strategies. Finally, future research recommendations are presented. Through the review, we find that the comfort models used in research are mostly based on comfort perception votes collected from experimental studies, which may not reflect the preferences of users well. In addition, only the influence of environmental factors on the models has been investigated, and other personal factors have been ignored. This study presents a useful guide for researchers to determine their outlines for future research in this field.

Optimization of environmental performance is one of the standards to be achieved towards designing sustainable buildings. Many researchers are focusing on zero emission building; however, it is essential that the indoor environment favors the performance of the building purpose. Empirical research has demonstrated the influence of architectural space variables on student performance, but they have not focused on holistic studies that compare how space influences different academic performance, such as Mathematics and Arts. This manuscript explores, under self-reported data, the relationship between learning space and the mathematics and art performance in 583 primary school students in Galicia (Spain). For this, the Indoor Physical Environment Perception scale has been adapted and validated and conducted in 27 classrooms. The results of the Exploratory Factor Analysis have evidenced that the learning space is structured in three categories: Workspace comfort, natural environment and building comfort. Multiple linear regression analyses have supported previous research and bring new findings concerning that the indoor environment variables do not influence in the same way different activities of school architecture.

It is well known that buildings have a sizeable energy and environmental footprint. In particular, in environments like university campuses, the occupants as well as occupancy in shared spaces varies over time. Systems for cooling in such environments that are centrally controlled are typically threshold driven and do not account for occupant feedback and thus are often relying on a reactive approach (fix after identifying problems). Therefore, having a fixed thermal operating set point may not be optimal in such cases—both from an occupant comfort and well-being as well as an energy efficiency perspective. To address this issue, a study was conducted which involved development and deployment of an experimental Internet of Things (IoT) prototype system and an Android application that facilitated people engagement on a university campus located in the UAE which typically exhibits hot climatic conditions. This paper showcases data driven insights obtained from this study, and in particular, how to achieve a balance between the conflicting goals of improving occupant comfort and energy efficiency. Findings from this study underscore the need for regular reassessments and adaptation. The proposed solution is low cost and easy to deploy and has the potential to reap significant savings through a reduction in energy consumption with estimates indicating around 50–100 kWh/day of savings per building and the resulting environmental impact. These findings would appeal to stakeholders who are keen to improve energy efficiency and reduce their operating expenses and environmental footprint in such climatic conditions. Furthermore, collective action from a large number of entities could result in significant impact through this cumulative effect.