Search Results (134)

Smart living is strongly promoted to enhance the quality of life via the application of innovative solutions, and this is driven by domain specialists and policymakers, including designers, urban planners, computer engineers, and property developers. Nonetheless, the actual user, whose views ought to be considered during the design and development of smart living systems, has received little attention. Thus, this study aims to identify and examine the critical smart functions to achieve smart living in smart buildings based on occupants’ perceptions. The aim is achieved using a sequential quantitative research method involving a literature review and 221 valid survey data gathered from a case of a smart student residence in Hong Kong. The method is further integrated with descriptive statistics, the Kruskal–Walli’s test, and the criticality test. The results were validated via a post-survey with related experts. Twenty-six critical smart functions for smart living were revealed, with the top three including the ability to protect personal data and information privacy, provide real-time safety and security, and the ability to be responsive to users’ needs. A need was discovered to consider the context of buildings during the design of smart living systems, and the recommendation is for professionals to understand the kind of digital technology to be integrated into a building by strongly considering the context of the building and how smart living will be achieved within it based on users’ perceptions. The study provides valuable insights into the occupants’ perceptions of critical smart features/functions for policymakers and practitioners to consider in the construction of smart living systems, specifically students’ smart buildings. This study contributes to knowledge by identifying the critical smart functions to achieve smart living based on occupants’ perceptions of smart living by considering the specific context of a smart student building facility constructed in Hong Kong. Full article

This study aims to develop an information strategy plan (ISP) for the integrated management of airport facility information in South Korea by applying smart technologies such as building information modeling (BIM), digital twins, and openBIM. As the demand for intelligent lifecycle management and efficient facility operations continues to grow, airport infrastructure requires standardized and interoperable systems to manage complex assets and stakeholder collaboration. This research addresses three core challenges facing Korean airports: the lack of sustainable maintenance environments, the absence of data standards and systems, and the insufficiency of user-oriented platforms. Through system analysis, benchmarking, and SWOT assessment, the study proposes a stepwise implementation roadmap consisting of development, integration, and advancement phases and designs a “To-Be” model that incorporates 37 component technologies and a standardized information framework. The proposed ISP supports data-driven airport operations, enhances collaboration, and accelerates digital transformation, ultimately contributing to the development of smart and globally competitive airports. Full article

This study presents a comprehensive assessment of energy efficiency and conservation strategies in institutional buildings, using the Riyadh Reformatory Building (RRB) in Saudi Arabia as a case study. The analysis focuses on meeting the operational and safety requirements of the facility while aligning with the regulatory standards of the Saudi Arabian Standards Organization (SASO) and the Saudi Building Code (SBC Part 401), particularly in relation to electrical installations and the Energy Efficiency Ratio (EER) labeling system. Through simulation and evaluation, the study demonstrates that replacing traditional lighting with LED systems results in a 74% reduction in energy consumption. The application of programmable temperature regulators further reduces annual cooling energy use by 5.1%, with associated cost savings reaching 6.2%. Additionally, the research highlights the significant influence of window properties, thermal insulation, and water heater controls on energy performance. Notably, adopting high-EER air conditioning units leads to a 28.4% decrease in annual cooling energy consumption. Collectively, the findings underscore the effectiveness of integrated energy management practices, including optimized building layout, high-efficiency systems, and smart control technologies, in achieving substantial energy savings and operational cost reductions in institutional settings. Full article

Building information modeling (BIM) and thermal imaging from drone flyovers present innovative opportunities for enhancing building energy efficiency. This study examines the integration of BIM models with thermal data collected using unmanned aerial vehicles (UAVs) to assess and manage energy performance throughout a building’s lifecycle. By leveraging BIM’s structured data and the concept of the digital twin, thermal analysis can be automated to detect thermal bridges and inefficiencies, facilitating data-driven decision-making in sustainable construction. The paper examines methodologies for combining thermal imaging with BIM, including image analysis algorithms and artificial intelligence applications. Case studies demonstrate the practical implementation of UAV-based thermal data collection and BIM integration in an educational facility. The findings highlight the potential for optimizing energy efficiency, improving facility management, and advancing low-emission building practices. The study also addresses key challenges such as data standardization and interoperability, and outlines future research directions in the context of smart city applications and energy-efficient urban development. Full article

This article presents a comprehensive analysis of the potential for microgeneration of electrical energy from human physical activity and reviews current commercial and research solutions, including stationary bicycles, treadmills, rowing ergometers, strength equipment, and kinetic floor systems. The physiological foundations of human energy generation are examined, with attention to key factors such as age, gender, fitness level, maximum oxygen uptake, heart rate, and hydration. The study includes mathematical models of energy conversion from metabolic to electrical output, incorporating fatigue as a limiting factor in long-duration performance. Available energy storage technologies (e.g., lithium-ion batteries, supercapacitors, and flywheels) and intelligent energy management systems (EMS) for use in sports facilities and net-zero energy buildings are also reviewed. As part of the study, a conceptual design of a multifunctional training and diagnostic device is proposed to illustrate potential technological directions. This device integrates microgeneration with dynamic physiological monitoring and adaptive load control through power electronic conversion. The paper highlights both the opportunities and limitations of harvesting human-generated energy and outlines future directions for sustainable energy applications in fitness environments. A preliminary economic analysis is also included, showing that while the energy payback alone is limited, the device offers commercial potential when combined with diagnostic and smart fitness services and may contribute to broader building energy efficiency strategies through integration with intelligent energy systems. Full article

The continuous evolution of Internet of Things (IoT) technologies presents significant opportunities and challenges within the domain of engineering education. This paper introduces a novel and comprehensive framework that extends the established Engineering Design Process (EDP) by incorporating a modular Digital Twin (DT) structure specifically tailored to smart building IoT applications in education. Unlike previous approaches, our framework enables real-time system feedback, simulation-based design iteration, and hands-on experimentation—all integrated within a pedagogical flow aligned with engineering curricula. It comprises seven distinct phases, providing a complete methodology that guides learners from fundamental concepts to advanced applications, including data visualization, real-time simulation, and system optimization. To demonstrate the applicability of the proposed framework, we design and experiment with a practical use case related to a meteorological station and data, which incorporate IoT-enabled sensors, actuators, and microcontrollers for real-time monitoring of environmental parameters and energy consumption within a smart building campus facility. Additionally, to support EDP extension, a hybrid pedagogical approach is introduced, which combines traditional engineering hands-on education methodologies with DT activities, to further foster experimental learning, iterative system design, and complex systems thinking development. To this end, our approach aims to bridge the gap between theoretical science and engineering knowledge, along with practical application use cases, contributing to a better preparation of future engineers capable of addressing interdisciplinary challenges associated with smart systems and digital transformation within the Industry 4.0 era. Full article

In recent years, Facility Management has undergone significant technological and methodological advancements, primarily driven by Building Information Modelling (BIM), Computer-Aided Facility Management (CAFM), and Computerized Maintenance Management Systems (CMMS). These innovations have improved process efficiency and risk management. However, challenges remain in asset management, maintenance, traceability, and transparency. This study investigates the potential of blockchain technology and non-fungible tokens (NFTs) to address these challenges. By referencing international (ISO, BOMA) and European (EN) standards, the research develops an asset management process model incorporating blockchain and NFTs. The methodology includes evaluating the technical and practical aspects of this model and strategies for metadata utilization. The model ensures an immutable record of transactions and maintenance activities, reducing errors and fraud. Smart contracts automate sub-phases like progress validation and milestone-based payments, increasing operational efficiency. The study’s practical implications are significant, offering advanced solutions for transparent, efficient, and secure Facility Management. It lays the groundwork for future research, emphasizing practical implementations and real-world case studies. Additionally, integrating blockchain with emerging technologies like artificial intelligence and machine learning could further enhance Facility Management processes. Full article

With the intensification of aging, the imbalance between the supply and demand of elderly care services has become increasingly prominent. Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. Street view semantic segmentation technology was employed to extract street environmental elements in central urban areas, and a multiple regression model was established to elucidate the impact mechanisms of the built environment on walking accessibility. Key findings include: (1) Significant urban-rural service disparities exist, with 91.4% of urban core facilities offering seven service categories within 15-min walking catchments compared to 26.86% in township areas, demonstrating suburban infrastructure’s heavy reliance on administrative resource allocation. (2) Street environmental factors exhibit significant correlations with walking accessibility scores. At the 15-min walking threshold, building space ratio and transportation infrastructure coverage positively influenced walking convenience, while sky view ratio showed a negative correlation. (3) A random forest-based location prediction framework identified multiple service gaps in existing facilities. Suburban service deficiencies (e.g., 59.8% medical facility coverage within walkable catchments) emerge as critical equity barriers, prompting recommendations for integrated “micro-clinic + smart pharmacy” networks and prioritized mixed-use zoning in new urban planning. This research advances a data-driven framework for reconciling urbanization-aging conflicts, offering practical insights for developing nations in creating age-friendly urban environments. Full article

Smart buildings equipped with diverse control systems serve the objectives of gathering data, optimizing energy efficiency (EE), and detecting and diagnosing faults, particularly in the domain of indoor environmental quality (IEQ). Digital twins (DTs) offering an environmentally sustainable solution for managing facilities and incorporated with artificial intelligence (AI) create opportunities for maintaining IEQ and optimizing EE. The purpose of this study is to assess the impact of AI-driven DTs on enhancing IEQ and EE in smart building systems (SBS). A scoping review was performed to establish the theoretical background about DTs, AI, IEQ, and SBS, semi-structured interviews were conducted with the specialists in the industry to obtain qualitative data, and quantitative data were gathered via a computerized self-administered questionnaire (CSAQ) survey, focusing on how DTs can improve IEQ and EE in SBS. The results indicate that the AI-driven DT enhances occupants’ comfort and energy-efficiency performance and enables decision-making on automatic fault detection and maintenance conditioning to improve buildings’ serviceability and IEQ in real time, in response to the key industrial needs in building energy management systems (BEMS) and interrogative and predictive analytics for maintenance. The integration of AI with DT presents a transformative approach to improving IEQ and EE in SBS. The practical implications of this advancement span across design, construction, AI, and policy domains, offering significant opportunities and challenges that need to be carefully considered. Full article

Airport facility management requires innovative and coordinated techniques due to the infrastructure’s complexity, stakeholders’ diversity, and the necessity of safety. Adopting building information management (BIM) as an advanced technology has several benefits, including increased productivity, lower cost, and higher quality of service. This study seeks to determine the strategies for using BIM in airport facility management. In this vein, two questionnaires were developed to collect data based on a literature review. The first questionnaire was used to collect data for identifying and ranking the main criteria, and the second questionnaire was used to identify the practical strategies. The experts of this study answered five strengths, four weaknesses, five opportunities, and five threats using a standardized questionnaire. An integrated AHP-SWOT approach was used to identify and examine the practical strategies. Furthermore, a sensitivity analysis was used to ensure the results were correct. The findings showed that smart maintenance management, with a weight of 0.363, was the most important strength in the SWOT analysis. Resistance to change was the most important weakness, with a weight of 0.455. The increasing need for smart airports with a weight of 0.358 was the most important opportunity, while cybersecurity issues with a weight of 0.385 were the most important threat. Integrating BIM into the aviation sector can enhance efficiency and sustainability in airport facility management while addressing potential opportunities and shared hazards that extend beyond airport operations. Full article

As a result of the increase in the number of smart buildings and advances in technology, energy consumption in buildings has become increasingly important. The estimation of energy consumption in buildings is critical for energy efficiency. Accurate estimation of photovoltaic (PV) solar power plant efficiency is crucial for optimizing the performance of renewable energy applications. In this study, advanced machine learning regression models such as XGBoost, CatBoost, LightGBM, AdaBoost and Histogram-Based Gradient Boosting are used to predict PV efficiency based on ten internal features (Open Circuit Voltage (Voc), Short Circuit Current (Isc), Maximum Power (Pmpp), Solar Irradiation Spread (SIS), Maximum Voltage (Vmpp), Maximum Current (Impp), Fill Factor (FF), Parallel Resistance (Rp), Series Resistance (Rs), and Module Temperature (Tm)) of PV module measurements from the Utrecht University Photovoltaic Outdoor Test Facility. As a result, CatBoost outperformed the others, achieving the lowest prediction error MSE of 0.002 and the highest R² value of 0.90. To interpret the model’s predictions, we applied Explainable Artificial Intelligence techniques, in particular SHAP and LIME, which identify key features affecting efficiency and increase model transparency. The integration of these methods provides valuable insights for PV solar power plant design and optimization. Full article

The transition towards energy-efficient and sustainable buildings is a cornerstone of global efforts to combat climate change. Building automation and control systems (BACSs), standardized under EN ISO 52120, and the Smart Readiness Indicator (SRI) have emerged as pivotal tools for optimizing energy performance, integrating smart technologies, and enhancing building adaptability. This review provides a comprehensive analysis of the current research landscape and practical applications of these frameworks, focusing on their role in advancing energy efficiency, occupant comfort, and environmental sustainability. Key contributions include an exploration of challenges in SRI evaluation, considering the limitations of simplified methods, the need for long-term validation, and gaps in integrating advanced control functions. This study emphasizes innovative solutions for adapting SRI assessments to diverse building types, climate conditions, and regulatory frameworks. Furthermore, it presents original insights into leveraging advanced technologies, including Building information modeling (BIM) and digital twins (DTs), to refine SRI evaluation methods and optimize BACS designs. These findings contribute to the development of sustainable, intelligent buildings that align with EU climate goals. The authors conclude by highlighting promising directions for future research to further enhance smart energy and strategic facility management practices. Full article

Smart cities are confronted with a variety of disaster threats. Among them, natural fires pose a serious threat to human lives, the environment, and asset security. In view of the fact that existing research mostly focuses on the analysis of accident precursors, this paper proposes a dynamic risk-modeling method based on Stochastic Petri Nets (SPN) and Bayesian theory to deeply explore the evolution mechanism of urban natural fires. The SPN model is constructed through natural language processing techniques, which discretize the accident evolution process. Then, the Bayesian theory is introduced to dynamically update the model parameters, enabling the accurate assessment of key event nodes. The research results show that this method can effectively identify high-risk nodes in the evolution of fires. Their dynamic probabilities increase significantly over time, and key transition nodes have a remarkable impact on the emergency response efficiency. This method can increase the fire prevention and control efficiency by approximately 30% and reduce potential losses by more than 20%. The dynamic update mechanism significantly improves the accuracy of risk prediction by integrating real-time observation data and provides quantitative support for emergency decision making. It is recommended that urban management departments focus on strengthening the maintenance of facilities in high-risk areas (such as fire alarm systems and emergency passages), optimize cross-departmental cooperation processes, and build an intelligent monitoring and early-warning system to shorten the emergency response time. This study provides a new theoretical tool for urban fire risk management. In the future, it can be extended to other types of disasters to enhance the universality of the model. Full article

Retrofitting legacy systems provides significant advantages by addressing compatibility issues with new devices and technologies, meeting current process requirements, and increasing security and regulatory compliance. The process starts by collecting requirements and evaluating the legacy system’s attributes and limitations, followed by integrating modern technologies to improve efficiency, streamline processes, and enhancing performance and interoperability while leveraging existing facilities to reduce costs. A systematic approach ensures that updates align with modern technological standards, with performance evaluations conducted via qualitative and quantitative methods and system maturity assessed according to the Reference Architecture Model for Industries 4.0 (RAMI 4.0 model’s) criteria for intelligent factories. By incorporating digital twin (DT) capabilities, which replicate the physical state of systems and provide real-time data updates, the retrofit strategy aligns the physical system with Industry 4.0 contexts, facilitating continuous improvement and seamless integration with modern processes. The goal is to advance the legacy system technologically to ensure seamless integration with contemporary processes, validated through RAMI criteria analysis for smart factories. As part of this process, digital twin architecture was built. This architecture was the basis for building and operating digital twins in the process. The methodology was used to enhance and transform legacy systems, creating the foundation for creating a fully digital twin. Using this method, these systems can be updated to meet the requirements of Industry 4.0. This ensures that they can work with new systems and share data in real time, which improves general operations. Full article

The emergence of smart campuses marks a pivotal advancement in educational pedagogy, environmental quality, resource allocation, and administrative services. This study presents the conceptualization and implementation of the Nanxun Campus of Zhejiang University of Water Resources and Electric Power (ZJWEU), which serves as an exemplary smart water initiative. Adhering to the philosophy of integrating educational facilities within the campus infrastructure, the campus incorporates several specialized zones: a key protection area, the water conservation area, the ecological stability area, the living water spirit area, and the teaching and practice area. This study clarifies the unique attributes, design philosophies, and operational mechanisms of these distinct zones. Central to the campus’s identity is a water culture-centric strategy, with each building reflecting water-themed concepts and providing extensive real-world engineering teaching and practice environments. Since its opening in 2022, the campus has been admitting approximately 5000 students annually and has been a model of water culture campuses that integrate ecology, intelligence, humanism, and synergy. The insights and infrastructure provide a valuable reference and foundational support for the evolution of smart campuses, underscoring the potential to merge water culture with avant-garde educational practices. Full article