Smart Green Buildings Research Articles

Why do health-risk awareness and materialism drive consumers' acceptance intentions for smart green buildings?

As the threat of global warming to human beings has gradually received attention, this article introduces the terror management theory to explain whether health risk awareness will affect their willingness to accept smart green buildings and that relationship is positively regulated by death anxiety. In addition, this article introduces the concept of materialism to propose that consumers will also accept smart green buildings due to the influence of materialism. This article interviewed two consumers and two professors in Taiwan, and verified the three hypotheses of this article through qualitative coding analysis. This article also used quantitative research methods to verify the theoretical model. This article not only introduces the cross-cutting contributions between terror management theory, materialism and smart green buildings, but also helps the construction industry develop strategies to attract consumers.

A REVIEW OF SMART GREEN BUILDING TECHNOLOGIES: INVESTIGATING THE INTEGRATION AND IMPACT OF AI AND IOT IN SUSTAINABLE BUILDING DESIGNS

This scholarly paper delves into the dynamic realm of smart green building technologies, focusing on the integration and impact of Artificial Intelligence (AI) and the Internet of Things (IoT) within the sphere of sustainable architecture. The study is anchored in the background of evolving green building principles, underscored by the burgeoning rise of smart technologies that are reshaping modern architectural practices. Aimed at comprehensively understanding the transformative role of AI and IoT in enhancing building performance and sustainability, the paper adopts a ethodological approach centered on an extensive literature review and qualitative analysis. It meticulously examines the synergy between AI and IoT, their implementation challenges, environmental and social impacts, and the economic implications of investing in such technologies.The main findings reveal that the integration of AI and IoT significantly elevates energy efficiency, optimizes building performance, and contributes to environmental sustainability. The study highlights innovative IoT solutions in building management, demonstrating their effectiveness in creating more efficient and sustainable living spaces. However, it also identifies barriers to the adoption of these technologies, including economic constraints and the need for skilled professionals.Conclusively, the paper recommends a multi-faceted approach to overcome these challenges, emphasizing policy interventions, educational initiatives, and the development of cost-effective green building technologies. The study underscores the need for collaborative efforts from various stakeholders to advance sustainable architecture and building management.This paper provides a comprehensive exploration of the integration of AI and IoT in sustainable building designs, offering insights into their potential to revolutionize the construction industry and pave the way for sustainable urban development.
 Keywords: Smart Green Building Technologies, Artificial Intelligence, Internet of Things, Sustainable Architecture, Energy Efficiency, Building Performance.

The impact of thermal insulating materials in heat loss control in smart green buildings using experimental and swarm intelligent analysis.

The efficacy of saving energy standards depends on the ability to anticipate the heat loss of buildings. Environmentally friendly materials, also known as eco-friendly or sustainable materials, have a minimal negative impact on the environment throughout their life cycle. These materials are designed to conserve resources, reduce pollution, and promote sustainability. The characteristics of non-stationary and non-linear heat loss through environmentally friendly materials make it challenging to anticipate accurately. At the same time, many of the industry's presently accessible computational models have been created with this in mind; the majority call for powerful computers and time-consuming computations. The artificial neural network (ANN) has been utilized for prediction, and ground-breaking research has shown the viability of this strategy. This research proposes an artificial neural network (ANN) prototype to estimate construction cooling load usage. ANN is integrated with the vortex search algorithm (VS), stochastic fractal search (SFS), and multi-verse optimizer (MVO) models to compare the three models' outcomes and suggest a more accurate strategy. These techniques make a linear mapping among the output and input parameters, often utilized for modeling and regression. The value of the multiple determination coefficient is also determined. The values of the training R2 (coefficient of multiple determination) are 0.9464, 0.99827, and 0.99522 for VS-MLP, SFS-MLP, and MVO-MLP, respectively, with an unknown dataset which is acceptable. The training RMSE amounts for VS-MLP, SFS-MLP, and MVO-MLP are 0.06433, 0.00619, and 0.01028 for the unknown dataset, which is acceptable. According to the MAE values of 0.0082902, 0.0047834, and 0.0076534 in the training phase for VS-MLP, SFS-MLP, and MVO-MLP approaches and the values of testing MAE error of 0.029107, 0.018167, and 0.029212 for VS-MLP, SFS-MLP, and MVO-MLP approaches, respectively, it is obtained that the SFS-MLP has a lower MAE value. The lowest RMSE value and the higher R2 value indicate the favorable accuracy of the SFS-MLP technique.

Integrated long reach and energy-efficient NGPON-VLC system with OCDM/WDM for smart green buildings

Smart green buildings (SGBs) are composed of numerous services and offer hopeful solutions to the world's continuous and rapid urbanization. Conventional data transmission systems are insufficient to deliver acceptable services because to the sudden surge in high-quality information transmission requirements over long distance for numerous linked residents in SGBs. Consequently, a hybrid next generation passive optical network (NGPON) along with visible light communication (VLC) indoor/outdoor broadcast network is presented in this work to increase the reliability with intelligence, exalted overall efficiency, cost efficiency, and security of SGBs. Bidirectional PON-VLC system incorporates the time and wavelength division multiplexing (TWDM), wavelength division multiplexing (WDM) and optical code division multiplexing (OCDM) techniques. In order to improve system performance, various OCDM codes are used in this work at 10/2.5 Gbps per channel throughput via fiber-VLC channels. According to the simulation results, the modified new zero cross-correlation (MNZCC) code performs better than previous codes and supports 200 active residents at reliable 100 km fiber along with 5 m VLC range. Furthermore, by expanding the received aperture diameter to 25 cm, VLC coverage may be increased till 10 m. Moreover, it provides adequate receiver sensitivities of − 13 to − 12 dB in uplink with − 9.8 to − 6 dBm in downlink for 200 to 600 fields of view angles compared to 00 view angle having sensitivity of − 15 dBm. Additionally, the numerical analysis and comparison performance show that PON-VLC outperforms fiber-VLC link-based scenarios when it comes to noise and channel impairments.

A Literature Review on the Application of Ibeacon in Education Settings

With the advent of iOS 7, a new technology from Apple called iBeacon appeared, iBeacon made a significant step forward in the Internet of Things (IoT) (Townsend, 2023). As technology is becoming a more central part of people’s lives, people’s devices start to talk to each other more and iBeacon helps a device figure out what is nearby and what it can talk to. Currently, iBeacon is also widely applied in education settings, which promotes heated discussion on its potential in education sector application (Spachos & Mackey, 2018), many publications have also been issued in the academia on the application of iBeacon in education settings, but so far, there has not been any review on these studies. This article presents a literature review of the studies on the application of iBeacon in education settings published from 2016 to 2020, aiming to discuss the widespread application of iBeacon in educational contexts, and shed light on its innovative potential and revolutionary potential; the discussions on using iBeacon in smart green building courses, context-aware ubiquitous learning environments, flipped classroom learning, and smart campus classroom attendance system show that iBeacon can efficaciously support teachers’ instructional activities and students’ learning activities, help teachers quickly obtain students' learning situation in classroom and then may adjust their instructional approaches or contents, and help pupils effectually engage with their daily learning and develop their learning skills.

Multi-objective optimization of IoT-based green building energy system using binary metaheuristic algorithms

Green building energy optimization systems (GBEOS) are of great interest to academics and industry professionals. One of the main challenges of GBEOS is optimizing energy consumption while maintaining people's comfort level. This paper proposes a metaheuristic-based GBEOS for optimizing energy consumption within a smart green building operating under a smart grid paradigm while considering the local environment and energy demand behaviors. In this regard, two complementary control procedures are developed: the supply-part optimizer (SPO) and the demand-part optimizer (DPO). By combining SPO and DPO, six binary multi-objective optimization algorithms, including Xtreme gradient boosting (XGBoost), multiverse optimizer (MVO), moth flame optimization (MFO), shuffled frog leaping algorithm (SFLA), moth flame optimization, imperialist competitive algorithm (ICA), and chimp optimization algorithm (ChOA) are developed to simultaneously minimizes costs and maximizes client comfort satisfaction (CS). First of all, considering the importance of convergence speed, seven unimodal, six multimodal, and twenty complex benchmark optimization functions are used to evaluate the proposed approach's convergence behavior. Afterward, an efficient weighting mechanism is used to handle the cost-comfort trade-off, allowing the user to discover a reasonable trade-off between monetary expense and comfort level. Then, in order to determine the influence of the pricing scheme's nature on the potential savings achieved through EMS, three individual models named real-time pricing (RTP), time-of-utilize pricing (TUP), and fixed-pricing plan (FPP) are proposed. The results show that ChOA presents the best result in terms of convergence, with 19 out of 33 test functions; also, XGBoost has the second-best performance. In addition, results show that suggested metaheuristic algorithms significantly increase PV energy penetration for self-consumption and lower power costs while keeping an optimal balance between CS and economical costs. Moreover, using dynamic pricing systems, i.e., RTP or TUP, results in great user price savings than FPP. To sum up, ChOA is found to be the best algorithm in this challenge, followed by XGBoost in second place.

Digital Twins for Intelligent Green Buildings

At present, the integration of green building, the intelligent building industry and high-quality development are facing a series of new opportunities and challenges. This review aims to analyze the digital development of smart green buildings to make it easier to create contiguous ecological development areas in green ecological cities. It sorts out the main contents of Intelligent Green Buildings (IGB) and summarizes the application and role of Digital Twins (DTs) in intelligent buildings. Firstly, the basic connotations and development direction of IGB are deeply discussed, and the current realization and applications of IGB are analyzed. Then, the advantages of DTs are further investigated in the context of IGB for DT smart cities. Finally, the development trends and challenges of IGB are analyzed. After a review and research, it is found that the realization and application of IGB have been implemented, but the application of DTs remains not quite integrated into the design of IGB. Therefore, a forward-looking design is required when designing the IGBs, such as prioritizing sustainable development, people’s livelihoods and green structures. At the same time, an IGB can only show its significance after the basic process of building the application layer is performed correctly. Therefore, this review contributes to the proper integration of IGB and urban development strategies, which are crucial to encouraging the long-term development of cities, thus providing a theoretical basis and practical experience for promoting the development of smart cities.

A comprehensive review on emerging trends in smart green building technologies and sustainable materials

The use of environmentally friendly materials in construction has become increasingly possible due to advancements in green technology. There are several sustainable materials derived from industrial waste that aid in reducing embodied energy and maximizing the use of renewable resources. Technology is the key to successful projects that advance green building. Various green building technologies with temperature reduction, wastewater systems, energy efficiency, photovoltaic powered cooling system, etc are represented in this paper. In green building, a building information model (BIM) and ontology are used to manage multi-disciplinary activities. SWRL and OWL models based on the Jess rule engine are combined to improve building efficiency. Sustainable materials which are obtained from industrial waste help to reduce the carbon footprint on the environment. The strength, workability, and density of these materials are increased by the usage of various activators. Smart materials operate based on external factors such as sensors, weather conditions, and so on. Smart materials are used in the Electro-Mechanical Impedance (EMI) approach to detect structural flaws in a structure. In smart homes, technology can be used to control energy consumption. Shape Memory Alloys, fiber optics, piezoelectric materials, magnetorheological fluids, and electro-rheological fluids are examples of smart materials used in smart, sustainable urbanization. The Internet of Things (IoT) developed a method for collecting construction data that reduced the structure's cost. The research will recommend appropriate techniques and materials for the Indian scenario to achieve long-term sustainable goals for the country.

Potential building energy savings by passive strategies combining daytime radiative coolers and thermochromic smart windows

Reducing the energy consumed by space cooling and providing outstanding thermally insulated windows are essential requirements for a smart green building. In this study, a new building design concept for envelope/façade is proposed and demonstrated, providing a solution for thermal management in buildings. This new design for the envelope/façade of buildings comprises two major passive and energy-free technologies, a daytime radiative cooler and a thermochromic smart window. The PDMS-silica-silver daytime passive radiative cooler can provide a cooling effect to the indoor environment without energy input, meanwhile the thermochromic smart window using PNIPAm hydrogel can passively modulate the solar irradiance entering buildings through windows. Hence, the energy needed for indoor heating, cooling and lighting can be reduced significantly. To evaluate the energy-saving performance, model houses are built, one of which is assembled using the proposed building design. The orientation effect on the indoor air temperature of the model houses is investigated. Under intensive solar irradiance, a maximum reduction of 4.8 °C of the indoor air temperature is achieved in the model house constructed using the proposed building design. An energy saving of about 17% of air-conditioning systems in buildings constructed with this new design is expected during daytime operation.

Preface

The International Conference on Science & Technology (2nd ICoST 2020) is an annual conference organized by Hemispheres. This year, the conference has been held on November 28, 2020. Hemispheres is committed to keeping the conference going even in difficult times due to the COVID-19 outbreak. This affected the implementation of this conference, which was originally offline due to large-scale restrictions and transportation policies, causing this conference to be held virtually. However, this conference was still well organized.It is predicted that the corona virus pandemic will change the pattern of human life and the environment for a long time. The world of science and technology also cannot be separated from this influence. Long distance interaction and digital life will be a way of socializing. Challenges and ways to survive in difficult conditions make human creativity try to solve these problems. This prompted Hemispheres to take up the theme at this year’s conference entitled “Challenges of globalization in the Pandemic Era”. The papers included in this conference consist of predictive modeling and monitoring device prototyping of COVID-19, identification, classification and detection of diseases, development of smart green buildings, design of SIMO converters for mitigation, use of algorithms and other computational methods. Hopefully the papers in this conference will be able to contribute to the literature on the challenges in this pandemic era. Editor of the 2020 2nd ICoST Ferry Wahyu Wibowo ORCID ID: 0000-0003-1913-436X Committee 2020 2nd International Conference on Science & Technology (2nd ICoST 2020) List of Committee, Steering Committee, Organizing Committee and Committee Members are available in the pdf

Feasibility Study on the implementation of room control automation to realize smart green buildings

Currently, the level of carbon dioxide (CO2) emissions is at the highest level. One of the causes is the waste of electricity used. One of the most significant contributors to electrical energy consumption is in the High Rise Building (HRB) sector. This paper proposed an automation system in Heating, Ventilation, and Air Conditioning (HVAC) systems, lightings systems, and electronic systems, especially in the guest room area, where electrical energy consumption very much depends on the guest’s behavior. The purpose of the proposed system is to save energy and to realize smart green buildings. The result shows that the proposed system provided an average energy saving of 294.882 kWh per month. This system could save the cost of electricity bills by 21,38% each month. Those results confirmed that the implementation of a room control automation system is feasible to realize smart green buildings.

Dielectric Elastomer Actuator-Based Multifunctional Smart Window for Transparency Tuning and Noise Absorption

Soft actuators are compliant material-based devices capable of producing large deformation upon external stimuli. Dielectric elastomer actuators (DEA) are a type of soft actuator that operates on voltage stimuli. Apart from soft robotics, these actuators can serve many novel applications, for example, tunable optical gratings, lenses, diffusers, smart windows and so on. This article presents our current work on tunable smart windows which can regulate the light transmittance and the sound absorption. This smart window can promote daylighting while maintaining privacy by electrically switching between transparent and opaque. As a tunable optical surface scatters, it turns transparent with smooth surfaces like a flat glass; but it turns ‘opaque’ (translucent) with the micro-rough surface. The surface roughness is varied employing surface micro-wrinkling or unfolding using dielectric elastomer actuation. Moreover, this smart window is equipped with another layer of transparent micro-perforated dielectric elastomer actuator (DEA), which acts like Helmholtz resonators serving as a tunable and broader sound absorber. It can electrically tune its absorption spectrum to match the noise frequency for maximum acoustic absorption. The membrane tension and perforation size are tuned using DEA activation to tune its acoustic resonant frequency. Such a novel smart window can be made as cheap as glass due to its simple all-solid-state construction. In future, they might be used in smart green buildings and could potentially enhance urban livability.

Using Intelligence Green Building Materials to Evaluate Color Change Performance

Environmental protection is an important issue in modern society. Most construction demolition wastes cannot be easily decomposed, thus occupying a lot of space in landfill. Reducing the demand for new resources is an efficient approach to decrease the environmental burden. Most green buildings are made from reused and recycled materials. Although there are a variety of green building materials available on the market, there is no material, as yet, with thermochromic functionality. This study used a form of face bricks, and six recovered materials, including wood chips, iron powder, fallen leaves, concrete, newspaper, and silt, to make smart green building materials. The modules were made in accordance with Taiwan’s green building material regulations. The discoloration efficiency of indoor and outdoor green building materials was tested, and the RGB (red, green, blue) values of the face bricks were measured by a color analyzer to observe the discoloration effect. The findings show that among the A, B, C, and D groups, Group D exhibited the optimal rate of change in color, and the rates of change in the six recycled waste materials of indoor Group D were wood chips > newspaper > fallen leaves > concrete > iron powder > silt, while the rates of change in the outdoor group were newspaper > wood chips > fallen leaves. This study successfully reused waste materials to reduce the environmental burden, achieve sustainable environmental protection, and ensure both the aesthetics and quality of the building materials. The results of this study can offer an alternative choice to architects or space designers when selecting green building materials.

One step forward toward smart city Utopia: Smart building energy management based on adaptive surrogate modelling

This study steps into the roadmap of agenda 2030 to mitigate the human footprint on an environment with the aim of management of energy consumption in residential/commercial buildings. In order to materialize this concept, a new generation of adaptable systems of intelligent supervisory predictive control (ISPC) is introduced and implemented in which energy consumption tends to be minimized without sacrificing occupants thermal comfort. The methodology of ISPC includes building thermal simulation and multi-objective optimization algorithm that interact with conventional machine-level controllers of HVAC systems, to define optimized setpoints considering current and forecasted operation conditions. The development of a reliable surrogate model, based on robust machine learning techniques, is a key feature to confer greenness to a building in order to promote sustainability in the built environment and finally to have a smart green building. It is showed that the proposed ISPC is capable of delivering a robust, energy- and cost-effective decision while being independent of the HVAC system. The implemented energy management, as a non-destructive retrofitting procedure, can be applied to both new and existing buildings and with any level of HVAC technology.

An Energy-Efficient Elevator Operating System that Considers Sensor Information and Electricity Price Changes in Smart Green Buildings

In modern smart buildings, the energy consumption of a building is monitored every time. Smart buildings are also equipped with sensors that can collect various physical data such as temperature, motion, and light. In this paper, we use smart sensor technologies in the design of an efficient elevator operating system (EOS). Specifically, multiple sensor devices are used together to detect elevator passengers’ behavior before they arrive at the elevator door and press the elevator call button. The detected information is then delivered to EOS through building networks and the scheduling system utilizes this information for the efficient control of the elevator cars. Specifically, when the number of passengers becomes large, EOS increases the number of working elevator cars to reduce the waiting time of passengers. In contrast, when the elevator traffic lessens, EOS reduces the number of working elevator cars in order to save the energy consumption. Experimental results with a wide range of configurations show that our EOS outperforms the conventional elevator scheduling system that does not consider sensor information or electricity price changes.

(Invited) Inkjet Printed Multifunctional Smart Windows

Electrochromic smart windows that are able to dynamically control the light and heat transmission into a building have attracted intense interests in the field of green building. However, currently external energy consumption is required for electrochromic smart windows to change their optical properties such as transmittance, reflectance and absorption. How to recycle the energy expended and finely integrate the multifunctional smart window are still challenging at present. With our earlier established work on the various of electrochromic nanomaterials such as NiO, WO3 on transparent conductors such as ITO, FTO, silver grid/PEDOT substrates, the importance and progresses of multifunctional smart window have been highlighted.1-4 We extended our efforts on large size multifunctional smart windows (more than 300 cm2) fabricated by inkjet printing technique which is one of the low cost and solution processible methods. The assembled electrochromic windows exhibit outstanding performance including large optical modulation, high coloration efficiency, fast switching and excellent bistability. The designed multifunctional smart window can be used as typical electrochromic window as well as energy-storage device. The smart window is able to change its color to dynamically control the light and heat into a building and store the energy in the day time, and then releases the stored energy to power other electronic devices at night. Moreover, we can monitor the level of stored energy in the window via the visually detectable reversible color variation. The reported multifunctional smart window represents a leap towards the realization of fascinating and energy-efficient smart green building. References (1) Cai, G.; Wang, X.; Cui, M.; Darmawan, P.; Wang, J.; Eh, A. L.-S.; Lee, P. S. Nano Energy 2015, 12, 258. (2) Cai, G.; Wang, J.; Lee, P. S. Acc. Chem. Res. 2016, 49, 1469. (3) Cai, G.; Darmawan, P.; Cui, M.; Chen, J.; Wang, X.; Eh, A. L.-S.; Magdassi, S.; Lee, P. S. Nanoscale 2016, 8, 348. (4) Cai, G.; Darmawan, P.; Cui, M.; Wang, J.; Chen, J.; Magdassi, S.; Lee, P. S. Adv. Energy Mater. 2016, 6, 1501882.

Energy-efficient vertical transportation with sensor information in smart green buildings

In modern smart green buildings, sensors can detect various physical status of a building such as temperature, humidity, motion, and light, which can be used for smart living services. This paper presents an energy-efficient vertical transportation by making use of indoor sensor technologies. Specifically, sensors detect elevator users before they push the call button, and then inform to the elevator control system through building networks. By using this information, our system generates a reservation call and controls the moving time and direction of each elevator efficiently. Simulation experiments with a variety of traffic situations show that our elevator control system exhibits significantly better performance than the conventional system that does not use sensor information with respect to passengers’ waiting time and energy consumption.

스마트 그린빌딩 구현을 위한 다기능 센서 통합 모듈 시스템 개발

Green IT technology for the growth of low-carbon green environment and future development of the new technology. Therefore, in this paper, data generated by the security module for RFID applications, smart green building Sung multi-function sensor integrated module that can be integrated environment for building monitoring and management system has been developed. The development of a thermal sensor, temperature sensor, smog sensor, CO2 sensor, O2 sensor, tension sensor and damage detection sensor module with integrated system module integrated multi-functional sensors implemented in the paper. In real-time monitoring by allowing was design and developed system that can be implemented smart green building environment for the environment inside buildings.

Smart Green Buildings of Tomorrow

Fast population growth and rapid development of our communities have exerted a huge impact on our natural environment. The design, fabrication, construction and operation of buildings in which we live and work are responsible for significant consumption of our natural resources. Taking the United States as an example, buildings account for 39% of total energy use, 68% of total electricity consumption, 30% of landfill waste, 38% of carbon dioxide emissions and 12% of total water consumption [1] and China is catching up. In order to alleviate the problem, smart green buildings development could well be considered as one of the viable choices. As its name suggests, smart green buildings combine ‘‘smart’’ and ‘‘green’’ concepts. Green buildings are about resources efficiency, lifecycle effects and building performance while keeping the lowest impact to the environment. Smart buildings, in which the core component is an integrated building technology system, are about construction and operational efficiencies, enhanced management and occupant functions. Therefore, the environment, economy and society can benefit from smart green buildings by enhancing and protecting biodiversity and ecosystems, improving air and water quality, reducing waste streams, conserving and restoring natural resources. Besides, smart green buildings can reduce operating costs, improve occupant productivity, enhance asset value and profits and optimize life-cycle economic performance. They can also enhance occupant health and comfort, improve indoor air quality, minimize strain on local utility infrastructure and improve overall quality of life. From another viewpoint, the minimum function of traditional buildings is to provide a shelter. Strength, durability, cost on selecting building materials, planning and construction are focused by civil engineering while aesthetics, comfort and attention to fulfilling psychological needs of the occupant are stressed by architecture. However, smart green buildings seek to conserve and utilize natural resources, emphasize eco-friendly construction and minimize carbon footprint on a global scale. The trend of the development is that smart green buildings should manage to cater more for the needs of humans, with increasing magnitude of personalization. People will be in control of the environment and be able to tune it to their needs. A lot of research activities are being carried out to make our buildings smarter and greener. Absorption, adsorption and various advanced thermodynamic cycles could be considered as renewed interest in thermally activated cooling and heating systems. Micro-channel systems could help improve heat and mass transfer, leading to reduction of fluid inventories, material utilization and environmental impact. Integrating micro-channel systems into smart green buildings could make those buildings more energy efficient. Apart from that, integrating novel heat transfer fluids (e.g. nanofluid) [2] as well as improved heat and mass transfer devices into heating and cooling systems can also further reduce the energy consumption and ecological footprint of some building systems. A trigeneration process is another option to increase the efficiency in thermal and electric generation. Recently, the tri-generation system has been used for power generation and also for air-conditioning systems. Comparing with the co-generation system, tri-generation refers to district energy which can achieve a higher efficiency with a smaller environmental impact. With a

Smart Green Buildings of Tomorrow

Smart Green Buildings of Tomorrow