Smart Buildings Research Articles

Digital twins for smart building at the facility management stage: a systematic review of enablers, applications and challenges

PurposeDespite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.Design/methodology/approachA systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.FindingsThe study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.Practical implicationsThe findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.Originality/valueThis study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

BEET: Blockchain Enabled Energy Trading for E-Mobility Oriented Electric Vehicles

Renewable Energy Sources (RESs) are gaining considerable attention to reduce human dependence on fossil fuels and minimize harmful gases in our surroundings. Existing literature on energy trading focused on providing renewable energy to smart homes, smart buildings, and smart offices to fulfill their daily energy demands obtained from RESs. Besides, Electric Vehicles (EVs) use either power grid energy or a battery exchange mechanism to recharge their low EV batteries. The continuous use of power grids to recharge low EV batteries causes a significant load on power grids. Due to this, power grids are inadequate to fulfill the ever-increasing demands of EVs in the future. In this context, we propose a Blockchain Enabled Energy Trading (BEET) framework oriented EV charging. A system architecture of the BEET framework is presented to describe the functioning of each layer and its associated entities. We formulate an optimization problem that maximizes the revenue in the energy trading process using a knapsack optimization. Smart contracts are designed on the consortium blockchain network to sell and buy renewable energy to aggregators and from producers, respectively. Moreover, an EV charging mechanism is designed to intelligently allocate renewable energy to consumers at a low price. A comparative analysis is performed with state-of-the-art works in terms of charging price, revenue, throughput, and latency. The results indicate that the BEET framework outperforms compared to state-of-the-art works to address the renewable energy demand problem to realize E-mobility. It is clarified that the data considered in the experimental analysis were obtained from statistical simulations in realistic E-Mobility environment settings.

SPCL: A Smart Access Control System That Supports Blockchain

The access control system is a critical element in intelligent buildings. In this paper, we present SPCL, an innovative access control system designed to facilitate building entry through the use of mobile phones. Our system aims to provide a secure and convenient solution for building access, capitalizing on the widespread availability and capabilities of mobile devices. Additionally, we propose a lightweight authentication protocol to enhance security. The performance of the protocol is measured for different curves at different frequencies, proving that the protocol is more suitable for door lock systems than the benchmark protocol. In addition, we investigated the security and usability of SPCL. Finally, a comparison of the security of human-lock interfaces for smart locks and blockchain-based payment methods are discussed.

An Ontological Analysis for Comparison of the Concepts of Sustainable Building and Intelligent Building

An Ontological Analysis for Comparison of the Concepts of Sustainable Building and Intelligent Building

Call for Papers: IEEE Transactions on Automation Science and Engineering Special Issue on Automation and AI in Construction and Building

Call for Papers: IEEE Transactions on Automation Science and Engineering Special Issue on Automation and AI in Construction and Building

Internet of things-based study on online monitoring system of building equipment energy saving optimization control using building information modeling.

Smart building equipment monitoring is a well-established field focused on enhancing contemporary building comfort. The proliferation of Internet connectivity, facilitated by the internet of things (IoT), has transformed buildings from static structures into interactive environments. IoT has witnessed substantial growth across various aspects of daily life, from monitoring environmental conditions to managing building systems and storing data in the cloud. One critical application is the intelligent monitoring and control of building equipment, such as air conditioners, to optimize energy efficiency-a matter of increasing concern for building owners, design experts, and system integrators. Achieving comprehensive energy savings demands a meticulous approach to energy-efficient design and control. This paper's primary objective is to explore and analyze IoT-based energy-saving optimization techniques for intelligent building equipment, integrating building information modeling (BIM) technology. It particularly delves into the energy conservation control algorithm for air-conditioning systems. The research presents a challenge rooted in energy-saving optimization, established upon specific objective functions, followed by a detailed explanation of the energy-saving control algorithm. To validate their approach, the paper outlines a comprehensive experimental design. Over three sessions in August, they conducted control experiments in two distinct areas. Area 1 implemented the energy-saving control methodology discussed in the paper, utilizing virtual parameter enhancement mechanisms, while Area 2 adhered to conventional control methods. The results were enlightening. Area 1 demonstrated superior energy efficiency, consuming 735 kWh compared to Area 2's 819 kWh, signifying an impressive 11.43% reduction in energy consumption thanks to the optimized control strategy. This research underscores the practicality and significance of implementing IoT-based energy-saving strategies, with a focus on smart thermostats, HVAC controllers, and daylight sensors, in intelligent building equipment management to achieve substantial energy conservation gains.

Implementing digital innovations: Overcoming organizational challenges

While real estate owners play a significant role in advancing digitalization and sustainability within the sector, there's limited understanding of their innovation processes. This article aims to increase understanding on the innovation processes and dynamic capabilities in real estate owner organizations. The article examines a longitudinal case study within a prominent Swedish real estate owner known for significant investments in smart building technologies. Despite these investments, practical benefits face hurdles, reflecting broader challenges in real estate sector digitalization projects. These obstacles include top-down innovation focus, limited cross-functional and user-centric innovation, innovation process discontinuities, ambiguous innovator roles, hierarchical communication, resource constraints, and uncertainties in technology implementation. The study emphasizes the inclusion of diverse perspectives in innovation processes and suggests further research on organizational and user-centric aspects. It contributes to real estate and facility management literature by proposing potential solutions to innovation processes, offering valuable insights for industry practitioners and researchers alike.

An agent-based evolutionary system model of the transformation from building material industry (BMI) to green intelligent BMI under supply chain management

The building materials industry ranks first in terms of carbon emissions and energy consumption within the industrial sector. To achieve the goal of reducing carbon emissions, the development of the green intelligent building materials (GIBMs) industry has become a strategic priority and major demand for the country. Government support plays a vital role in promoting the growth of the GIBMs industry. This paper utilizes evolutionary game theory and Matlab software to analyze the impact of government regulations on the development of the GIBMs industry. The research findings indicate the following. i) Appropriate government control over building materials enterprises is beneficial for the advancement of the GIBMs industry. A balance is necessary, as both excessive control and weak control hinder the industry’s development. ii) Increased financial assistance from the government to enterprises producing GIBMs has a positive influence. This support enables building materials enterprises to overcome technical barriers, drive technological innovation, and encourage construction developers to actively purchase these materials. iii) Stronger government punishment for pollutant emissions by building materials enterprises serves as a catalyst for the production of GIBMs. Stricter penalties motivate these enterprises to adopt more environmentally friendly practices. iv) Moderate to strong government investment in infrastructure has a significant impact. It prompts construction developers to actively choose and purchase GIBMs. In response to government regulations and market demand, building materials enterprises are inclined to produce these environmentally friendly materials. This study emphasizes the importance of government regulations and support in promoting the growth of the GIBMs industry. By implementing appropriate control measures, providing financial assistance, imposing punishments for pollution, and investing in infrastructure, the government can effectively encourage the development of the GIBMs industry. These measures contribute to achieving the double carbon goals and fostering a more sustainable built environment.

Green building energy: Patents analysis and analytical hierarchy process evaluation

In the dynamic sphere of building energy systems, this study explores advancements in energy integration, storage technologies, management practices, and occupant behavior, assessing sustainable energy practices, including emerging technologies like fuel cells and energy storage systems. It underscores the significance of efficient energy management, considering both renewable and conventional energy mechanisms. The study comprises four key strata: (i) a thorough literature review of recent energy trends, (ii) a comparative study of global energy patents using the World Intellectual Property Organization (WIPO) database, (iii) a comprehensive analysis of building-energy patents, and (iv) expert-guided Analytic Hierarchy Process (AHP) evaluation. These realms encompass five primary sources: (i) energy-efficient building design, (ii) intelligent building automation, (iii) optimizing energy systems integration, (iv) energy storage, and (v) energy management and optimization. Findings reveal energy storage's dominance, with water energy storage and emerging hydrogen technology leading the trajectory. Global energy patent scrutiny underscores China, the United States, and Japan as influential players in optimizing energy markets. The research shapes energy futures, identifies gaps, and drives sustainable energy practices within the built environment, serving as a compass for policymakers and researchers.

Barriers to the implementation of energy-efficiency practices in the U.S. retail sector: facilities managers’ perceptions compared by facility size and business revenue

PurposeThe retail sector has the largest energy consumption among commercial buildings in the U.S. Although previous studies explored benefits, barriers and solutions for implementing sustainability in various building sectors, research focused on retail facilities has been very scarce. This study aims to explore U.S. facilities managers’ perceptions of barriers that prevented the implementation of energy-efficiency practices in the retail sector. Their perceptions were compared by facility size and facilities management company’s business revenue.Design/methodology/approachAn online survey was distributed to the members of the International Facility Management Association and the author's LinkedIn network. The survey responses were analyzed using descriptive statistical analysis and ANOVA.FindingsManagers from large facilities, as opposed to those from small ones, significantly more agreed that the unavailability of building automation systems, a lack of professional writing skills and a lack of awareness of life cycle cost (LCC) were the barriers. Business revenue did not cause significantly different perceptions of the barriers except for a lack of awareness of LCC and a lack of support from upper management.Originality/valueThis study fills the research gap on energy efficiency in the retail sector by revealing U.S. facilities managers’ perceptions of the barriers to the implementation of energy-efficiency practices in retail stores. This novel study compares perceptions of the facilities managers by facility size and business revenue; this comparison has not been performed before. The study also identified several new barriers to the implementation of energy efficiency in the retail sector.

Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

The life cycle cost of a building is affected by the heating, ventilation, and air conditioning (HVAC) system chosen by the Life Cycle Costs (LCC). Quality, constructability, appearance of the structure's interior and exterior, HVAC size and weight, and LCC are some of the criteria influencing the choice. Methods: To monitor a project's progress based on energy savings, standard measures such as cost variance (CV) and schedule variation have used an idea when tracking the performance of intelligent buildings. Also, as described in the article, this research compared the decision-making limits of Building Information Modelling (BIM) and (MCDM). Analysis: The conventional approach cannot reveal information regarding divergence from the expected level of performance. Based on the outcomes of the construction cost variables, the key finding was the observation of 12 efficient elements. Finding and Novelty: According to the R, a building's most valuable features are its (Energy Saving Features, Warranties, Budget, Protect Your Unit, SEER Ratings, and Home Square Footage). The findings of Actual value (AV) and planned value (PV) were significantly different, as noted by the Multi-Criteria Decision Maker (MCDM). The new method also makes it possible to track project costs and timetables more accurately. The paper will characterize the HVAC Decision Support System's architecture (HVACDSS). Also, a case study of action modeling is provided, and the preliminary findings are addressed. Six criteria characteristics are used by the HVACDSS technique by an analysis of building construction conducted using the WEKA mining tool (decision tree).

Incorporating the Internet of Things (IoT) Learning Module into the Smart Building Course

The utilization of Internet of Things (IoT) devices is increasing very rapidly, creating a demand for skilled professionals who can navigate the complexities of this technology. It is a crucial educational challenge to prepare undergraduates to become contributors in this emerging field. The curriculum needs to be updated to offer students both theoretical learning and practical application so they can benefit from it. This paper introduces a comprehensive IoT learning module to the final-year students of civil engineering in an elective course, Smart Building. The proposed learning module includes an introduction to IoT concepts and applications, IoT devices, communication protocols, cloud platforms, user interfaces, and IoT risk management and security, all of which can be easily integrated into existing courses. Results from the module are presented using direct and indirect assessments, including assignments, hands-on practical, examinations, and surveys. These assessments are designed to evaluate the students’ understanding and the challenges they encountered in their IoT learning process. The findings indicate that a significant majority, surpassing 90% of the students, have demonstrated understanding of a minimum of three essential components of the fundamental IoT architecture, despite their limited background knowledge at the beginning of the course. Additionally, this learning module can serve as a valuable resource for other educators who intend to deliver IoT-related courses.

A comprehensive review of Building Energy Management Systems (BEMS) for Improved Efficiency

Building Energy Management Systems (BEMS) play a crucial role in enhancing energy efficiency and sustainability in buildings. This abstract provides a comprehensive review of BEMS, focusing on its components, benefits, challenges, and future trends. BEMS is a centralized system that monitors and controls building services, such as heating, ventilation, air conditioning, lighting, and other systems, to improve energy efficiency and occupant comfort. The key components of BEMS include sensors, controllers, communication networks, and user interfaces. These components work together to collect data on building performance, analyze energy consumption patterns, and optimize system operation. One of the primary benefits of BEMS is its ability to reduce energy consumption and costs. By monitoring and controlling building systems based on occupancy schedules and environmental conditions, BEMS can significantly reduce energy waste. Additionally, BEMS can improve occupant comfort and productivity by maintaining optimal indoor environmental conditions. Despite its benefits, BEMS faces several challenges, including high upfront costs, complexity of installation, and integration issues with existing building systems. However, advancements in technology, such as the Internet of Things (IoT) and cloud computing, are addressing these challenges and making BEMS more accessible and cost-effective. Looking ahead, the future of BEMS is promising, with continued advancements in technology driving its adoption and integration into smart building systems. The integration of artificial intelligence and machine learning algorithms into BEMS is expected to further improve its energy-saving capabilities and enhance building performance. In conclusion, BEMS is a key technology for improving energy efficiency and sustainability in buildings. By leveraging its components and capabilities, BEMS can help reduce energy consumption, lower costs, and create healthier and more comfortable indoor environments.

Sustainable facilities management in the built environment: a bibliometric review

Purpose This study aims to review the status quo, current state of research, research hot themes and research gaps in sustainable facilities management (SFM) in the built environment (BE) through an extant literature review. Design/methodology/approach To map and analyze knowledge paths in the context of SFM research, a sequential explanatory mixed-method review involving bibliometric and content analysis was used to help identify current research trends, research hot themes and knowledge gaps. The Scopus search engine was used to find 169 relevant articles. For a better understanding of the literature accumulated, a bibliometric analysis was carried out by using VOSviewer to reveal current research themes, the status quo and current state of research as well as research gaps. Findings Through the literature review and content analysis, the current research themes on SFM revealed from the study include green building technologies, assessment methods of SFM, smart buildings and building information modeling. The research hot themes in SFM include smart buildings and green building technologies, green buildings (GB), architectural and building designs in the university sector, assessment methods in buildings and decision-making and the adoption of asset and facility management in the university sector. Indoor air pollution, intelligent buildings, climate change, maintenance, environmental management, facilities, historic preservation, environmental performance, energy management, etc. are the research gaps identified from the study, and these serve as potential areas for future research studies under SFM. It was recognized that facilities managers are increasingly involved with sustainability policies within their organizations and are developing sustainability agendas to keep up with the changing nature of the facilities management (FM) profession. Practical implications The findings of this study hold relevance to the FM practice, as the integration of SFM by facilities managers can lead to waste reduction, decreased operating expenses and reduced energy consumption. In addition, occupants of sustainable buildings experience improved conditions that contribute to better health and productivity, thus boosting their overall well-being. Consistent with the themes of smart buildings and green technologies, revealed to be the hot themes in the SFM research scope, properties with sustainable features can command higher rental rates and property values, appealing to a broader range of stakeholders. SFM practices in universities can aid in saving money from reduced facility operational costs and improve the image of institutions while creating better indoor environments for students and staff. The analyses of countries involved in research can open doors for the establishment of research groups and the development of collaboration between universities in different countries researching similar topics of interest. Originality/value The geographical scope of this study is not limited and, therefore, encourages broad applicability of the findings to the global sustainable BE.

Digital methods in architectural and environmental renovation of buildings for a public function

This article explores advanced digital methods for comprehensive renovation of industrial buildings into public spaces. Four different approaches are described in detail: 1. Digital mapping and modeling: allows accurate spatial analysis to be performed for optimizing design solutions before physical renovation; combines virtual and augmented reality to create an immersive experience. 2. Integration of augmented and virtual reality: facilitates joint decision-making by visualizing proposed projects and thus increasing public engagement. Historical and cultural narratives are overlapped, strengthening the connection between the past and the present. 3. Smart building systems: include IoT devices and sensors to optimize energy efficiency, comfort, and overall functionality; solve unique challenges related to the conversion of industrial buildings. 4. Digital twin technology: creates a dynamic virtual copy for continuous real-time monitoring; uses machine learning for predictive analysis, increasing operational efficiency and sustainability. The convergence of technologies and architectural innovations presents a transformative force in the context of architectural and environmental renovation of industrial buildings, representing a change of the paradigm in the renovation of industrial facilities for re-use as a public function.

An edge information fusion perception network for curtain wall frames segmentation

Automatically detection of curtain wall frames is a crucial part of building automation. However, the current curtain wall installation robots mainly rely on manual assistance for positioning, resulting in low efficiency and inaccuracy. To address these drawbacks, we propose an edge information fusion perception network (EIFP-Net) for RGB-D curtain wall frames detection. Specifically, a cross-modal context fusion module (CCFM) allows fusing of RGB and depth features to enhance cross-modal information complementation and capture multi-scale context information simultaneously. In addition, an edge features sensing module (EFSM) is derived from the RGB branch, which is committed to realizing edge feature extraction. Within this module, a differential enhancement module (DEM) is introduced to enhance the edge information. Finally, a multi-scale progressive refinement decoder (MPRD) is designed to refine the features, utilizing the edge information as a guide to capture comprehensive features. The experimental results on the constructed curtain wall frame dataset show that the proposed EIFP-Net performs better than the state-of-the-art detection models, achieving 85.94 %, 88.29 %, 96.84 %, 86.81 %, and 87.10 % on the five evaluation metrics of precision, recall, accuracy, mIoU, and F1-score, respectively.

Hotspots and Frontier Analysis of Green Building Research based on CiteSpace

To examine the worldwide progress of green building and identify the areas of research focus and emerging trends over the last ten years, employed CiteSpace software to quantitatively analyze a selection of literature on green building from 2013 to 2023 in the WOS core collection. The key journals, major institutions and countries involved in the study were sorted out, and the research topics of literature high citation analysis were carried out. The research hotspots and frontiers were obtained through keyword co-occurrence, clustering, emergence and timeline analysis: 1) consumption, strategy, thermal performance, emissions are four words of the highest centrality; 2) The five major research topics are new building materials, sustainable development, green innovation, environmental impact, and building information model; 3) The combination of green building and intelligent building is the development trend; 4) Three frontier research directions are green finance, energy simulation and geopolymer concrete. Based on the above analysis, it can be concluded that: 1) Promote the further integration with BIM technology; 2) Sustainable development is still a hot topic; 3) Focus on the exploration of green building materials; 4) AI green buildings will become a trend.

A novel intelligent modeling and prediction of heat energy consumption in smart buildings

The rising cost and demand for energy have prompted several organizations to devise innovative methods for monitoring, managing, and conserving energy. Heat energy load prediction in smart buildings is critical for saving energy as well as for meeting energy demands. As the cost of energy and demand is increasing, people must find some way to control it and save energy. To overcome these issues, an intelligent energy management system needs to be developed to help individuals by predicting heat energy demand ahead of time and analyzing energy use patterns. This paper introduces a data-driven short-term heat energy consumption prediction for smart buildings by developing a hybrid deep learning model considering the capabilities of Convolutional and Recurrent Neural Networks. The proposed model extracts hidden patterns from actual data collected through sensors and also uses hand-crafted features to predict the heat energy demand accurately. The efficiency of the proposed model has been evaluated on real smart heat metering data, a case study in Denmark, having three kinds of buildings: single-family, apartment, and terraced houses. The extensive experimental results have been reported with real-world data by considering various evaluation metrics such as MAE, RMSE, MAPE and R2. The results are promising and outperformed other state-of-the-art methods.

Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors.

Smart buildings use advanced technologies to automate building functions. One important function is occupancy detection using Internet of Things (IoT) sensors for smart buildings. Occupancy information is useful information to reduce energy consumption by automating building functions such as lighting, heating, ventilation, and air conditioning systems. The information is useful to improve indoor air quality by ensuring that ventilation systems are used only when and where they are needed. Additionally, it is useful to enhance building security by detecting unusual or unexpected occupancy levels and triggering appropriate responses, such as alarms or alerts. Occupancy information is useful for many other applications, such as emergency response, plug load energy management, point-of-interest identification, etc. However, the accuracy of occupancy detection is limited by factors such as real-time occupancy data, sensor placement, privacy concerns, and the presence of pets or objects that can interfere with sensor reading. With the rapid development of IoT sensor technologies and the increasing need for smart building solutions, there is a growing interest in occupancy detection techniques. There is a need to provide a comprehensive survey of these technologies. Although there are some exciting survey papers, they all have limited scopes with different focuses. Therefore, this paper provides a comprehensive overview of the current state-of-the-art occupancy detection methods (including both traditional algorithms and machine learning algorithms) and devices with their advantages and limitations. It surveys and compares fundamental technologies (such as sensors, algorithms, etc.) for smart buildings. Furthermore, the survey provides insights and discussions, which can help researchers, practitioners, and stakeholders develop more effective occupancy detection solutions for smart buildings.

Security assessment and improvement of building ethernet KNXnet/IP protocol

KNXnet/IP is a KNX-building automation protocol that communicates through an IP network. It is mainly used in the field of smart home and building automation control, allowing remote access to KNX devices through an IP network, so that building functions can be managed and controlled anywhere through an Internet connection. However, with the development of smart homes and building automation, such physical devices based on IP communication are more and more frequently in contact with the Internet, resulting in more and more security issues for home devices and buildings exposed to the Internet. This paper uses the formal analysis method-colored Petri net (CPN) combined with the CPN Tools to model the KNXnet/IP protocol and analyze the protocol interaction process. Based on the Dolev-Yao attacker model, the security of the KNXnet/IP protocol is evaluated and tested, and it is verified whether there are three types of attackable vulnerabilities in the protocol: replay, tampering, and spoofing. After CPN modeling analysis and verification, it is found that tampering and replay vulnerabilities in the original protocol. Therefore, we introduce timestamp and hash to strengthen the security mechanism of the protocol, which ensures the integrity, confidentiality, and freshness of the security mechanism of the protocol. After the final analysis and verification, the improvement scheme proposed in this paper can effectively improve the security performance of the protocol.