Smart Buildings for A Sustainable Development

The use of sustainable technologies for buildings, with the goal of creating an environment for living and working that uses fewer resources and generates less waste, also aims to retrofit existing buildings to be more efficient in terms of energy and water. Many cities are following this way targeting both commercial and municipal buildings. These cities are called smart cities where all life processes and nerve centers of social life are read, in order to radically improve quality of life, opportunity, prosperity, social and economic development, thanks to the use of technology. This paper deals with the study of smart buildings within smart cities, namely the use in an integrated project of computer and telematics tools with automation organized systems and passive bioclimatic strategies in architecture, determining a socio-technical management of intelligent building. The article is the result of a research carded out within the framework of intelligent buildings in the last generation cities, such as those ones with zero emissions that are taking place in the Middle East countries （Dubai, Masdar, Tiajin, and Kochi）. The topic deals with the issues of building automation as a form of technological intelligence and the study of those smart technologies integrated into the building envelope that improve its performances, making it more sustainable. The research methodology has provided a bibliographic retrieval on the state of the art and the latest technological trends in the building field, later has followed a theoretical and comparative approach of the examined technologies, which led to the development of reasoning on operation, performance and functional capabilities of a building that is both sustainable and home automation, to arrive at the final concept of sustainable intelligent building, able to combine the artificial intelligence, home automation, and technological devices of the architectural project to enhance the building energy performance. In conclusion, the proposed result is that of an integrated intelligent building in which artificial intelligence will become part of the shell-building in order to achieve high levels of energy efficiency and thus environmental sustainability.

Systematic Analysis of Safety and Security Risks in Smart Homes

The revolution in Internet of Things(IoT)-based devices and applications has provided smart applications for humans.These applications range from healthcare to traffic-flow management,to communication devices,to smart security devices,and many others.In particular,government and private organizations are showing significant interest in IoT-enabled applications for smart homes.Despite the perceived benefits and interest,human safety is also a key concern.This research is aimed at systematically analyzing the available literature on smart homes and identifying areas of concern or risk with a view to supporting the design of safe and secure smart homes.For this systematic review process,relevant work in the most highly regarded journals published in the period 2016–2020(a section of 2020 is included)was analyzed.A final set of 99 relevant articles(journal articles,book sections,conference papers,and survey papers)was analyzed in this study.This analysis is focused on three research questions and relevant keywords.The systematic analysis results and key insights will help researchers and practitioners to make more informed decisions when dealing with the safety and security risks of smart homes,especially in emergency situations.

Smart Building Design to Improve the Energy Consumption at an Office Room

Buildings are becoming smarter as a result of a variety of advanced technologies that enable energy management, optimal space utilization, and smart surveillance for safety, among other things. Energy-efficient smart building ideas and execution are of great interest and top priority due to the building’s occupants’ misused and high-power consumption. This paper addresses the design and execution of an energy management system that includes a solar power system for generating power for the building’s needs and a PIR-based automation system for efficient power use. This project was carried out at the Military Technological College (MTC) in Muscat, in the system engineering department’s offices. This project seeks to generate power for the building’s energy needs using solar photovoltaic panels and reduce energy consumption within the office using a PIR-based automation system. The results demonstrate that after the breakeven point (the time it takes to recoup the initial investment), it can provide power to the building for another 17 years. The calculations and practical results presented in this study approve that the system is extremely helpful.

Heating-Cooling Monitoring and Power Consumption Forecasting Using LSTM for Energy-Efficient Smart Management of Buildings: A Computational Intelligence Solution for Smart Homes

Energy management in smart homes is one of the most critical problems for the Quality of Life(QoL)and preserving energy resources.One of the relevant issues in this subject is environmental contamination,which threatens the world's future.Green computing-enabled Artificial Intelligence(Al)algorithms can provide impactful solutions to this topic.This research proposes using one of the Recurrent Neural Network(RNN)algorithms known as Long Short-Term Memory(LSTM)to comprehend how it is feasible to perform the cloud/fog/edge-enabled prediction of the building's energy.Four parameters of power electricity,power heating,power cooling,and total power in an office/home in cold-climate cities are considered as our features in the study.Based on the collected data,we evaluate the LSTM approach for forecasting parameters for the next year to predict energy consumption and online monitoring of the model's performance under various conditions.Towards implementing the Al predictive algorithm,several existing tools are studied.The results have been generated through simulations,and we find them promisingforfutureapplications.

High-performance wood-based thermoelectric sponges for thermal energy harvesting and smart buildings

The development of renewable woods for power generation can help improve the energy efficiency of buildings,and promote the concept design and implementation of“smart buildings”.Here,with specific chemical treatment and hydrothermal synthesis,we demonstrated the practical value of natural wood for thermoelectric power generation in smart buildings.The prepared wood-based thermoelectric sponges show high Seebeck coefficients of 320.5 and 436.6μV/K in the vertical and parallel directions of the longitudinal channel of wood.After 500 cycles of the compressive strain at 20%,the corresponding Seebeck coefficients increase up to 413.4 and 502.1μV/K,respectively,which is attributed to the improved contact and connection between tellurium thermoelectric nanowires.The Seebeck coefficients are much larger than those of most reported inorganic thermoelectric materials.Meanwhile,the thermoelectric sponges maintain excellent thermoelectric and mechanical stability.We further modeled the application value of wood-based thermoelectric sponges in smart buildings for power generation.Relatively high thermoelectric electricity can be obtained,such as in Beijing with over 1.5 million kWh every year,demonstrating the great potential in thermal energy harvest and energy supply.

Research and Practice of Smart Power Consumption

As a vital part of a smart grid, smart power consumption enables real-time interaction between consumers and the grid. With improved management of the demand side and energy efficiency, smart power consumption plays an important role in emission reduction as well as the economic operation of the power grid. Meanwhile, it enhances the power grid to a larger scale infrastructure by the two-way transmission of energy and information. This paper introduces the research, practice and vision of smart power consumption in China.

IoT in Building Process:A Literature Review

The pervasive diffusion of digital technologies opened up to new concepts in managing and monitoring the processes occurring in our society.Information and Communication Technologies(ICTs)become enabling tools to rethink our way of living,consuming and producing goods and services.Among these,the Internet of Things(IoT)represents the disruptive technology that may redefine the stages of the building process to meet renewed environmental challenges.This new technological paradigm imports in the Architecture,Engineering and Construction(AEC)sector new and not-tectonic instances.In this context,the paper maps the experiences related to the use of IoT for managing the building process.Through a systematic literature review,the article highlights the potential benefits generable by a widespread integration of IoT in the AEC sector.In particular,the article has three purposes:defining the IoT infrastructure for its proper application in the AEC sector;identifying IoT main application domains;investigating the integration modalities.

Modeling Methods of 3D Model in Digital Twins

To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in the􀀀elds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

A location-based fog computing optimization of energy management in smart buildings:DEVS modeling and design of connected objects

Nowadays,smart buildings rely on Internet of things(loT)technology derived from the cloud and fog computing paradigms to coordinate and collaborate between connected objects.Fog is characterized by low latency with a wider spread and geographically distributed nodes to support mobility,real-time interaction,and location-based services.To provide optimum quality of user life in moderm buildings,we rely on a holistic Framework,designed in a way that decreases latency and improves energy saving and services efficiency with different capabilities.Discrete EVent system Specification(DEVS)is a formalism used to describe simulation models in a modular way.In this work,the sub-models of connected objects in the building are accurately and independently designed,and after installing them together,we easily get an integrated model which is subject to the fog computing Framework.Simulation results show that this new approach significantly,improves energy efficiency of buildings and reduces latency.Additionally,with DEVS,we can easily add or remove sub-models to or from the overall model,allowing us to continually improve our designs.

Smart residential energy management system for demand response in buildings with energy storage devices

In the present scenario,the utilities are focusing on smart grid technologies to achieve reliable and profitable grid operation.Demand side management(DSM)is one of such smart grid technologies which motivate end users to actively participate in the electricity market by providing incentives.Consumers are expected to respond(demand response(DR))in various ways to attain these benefits.Nowadays,residential consumers are interested in energy storage devices such as battery to reduce power consumption from the utility during peak intervals.In this paper,the use of a smart residential energy management system(SREMS)is demonstrated at the consumer premises to reduce the total electricity bill by optimally time scheduling the operation of household appliances.Further,the SREMS effectively utilizes the battery by scheduling the mode of operation of the battery(charging/floating/discharging)and the amount of power exchange from the battery while considering the variations in consumer demand and utility parameters such as electricity price and consumer consumption limit(CCL).The SREMS framework is implemented in Matlab and the case study results show significant yields for the end user.

Comprehensive review of modeling,structure,and integration techniques of smart buildings in the cyber-physical-social system

Smart buildings have been proven to be a kind of flexible demand response resources in the power system.To maximize the utilization of the demand response resources,such as the heating,ventilating and air-conditioning(HVAC),the energy storage systems(ESSs),the plug-in electric vehicles(PEVs),and the photovoltaic systems(PVs),their controlling,operation and information communication technologies have been widely studied.Involving human behaviors and cyber space,a traditional power system evolves into a cyberphysical-social system(CPSS).Lots of new operation frameworks,controlling methods and potential resources integration techniques will be introduced.Conversely,these new techniques urge the reforming requirement of the techniques on the modeling,structure,and integration techniques of smart buildings.In this paper,a brief comprehensive survey of the modeling,controlling,and operation of smart buildings is provided.Besides,a novel CPSS-based smart building operation structure is proposed,and the integration techniques for the group of smart buildings are discussed.Moreover,available busi-ness models for aggregating the smart buildings are discussed.Furthermore,the required advanced technologies for well-developed smart buildings are outlined.

Aseismic smart building isolation systems under multi-level earthquake excitations： Part II, energy-dissipation and damage reduction

Based on the performance results of the previously suggested smart building isolation systems （lst companion paper）, this following study verifies the control effects of the systems from the view point of energy dissipation and damage level metrics. Several different model cases of the strategically isolated multi-story building structures utilizing passive dampers and semi-active resettable devices are analyzed and the energy-based target indices are compared. Performance comparisons are conducted on statistically calculated story/structural hysteretic energy and story/structural damage demands over realistic suites of earthquake ground motion records, representing seismic excitations of specific return period probability. Again, the semi-active solutions show significant promise for applications ofresettable device, offering advantages over passive systems in the consistent damage reductions. The specific results of this study include the identification of differences in the mechanisms by which smart building isolation systems remove energy, based on the differences in the devices used. Less variability is also seen for the semi-active isolation systems, indicating an increased robustness.

Design and control optimization of energy systems of smart buildings today and in the near future

Buildings contribute to a major part of energy consumption in urban areas, especially in areas like Hong Kong which is full of high-rise buildings. Smart buildings with high efficiency can reduce the energy consumption largely and help achieve green cities or smart cities. Design and control optimization of building energy systems therefore plays a significant role to obtain the optimal performance. This paper introduces a general methodology for the design and control optimization of building energy systems in the life cycle. When the design scheme of building energy systems is optimized, primary steps and related issues are introduced. To improve the operation performance, the optimal control strategies that can be used by different systems are presented and key issues are discussed. To demonstrate the effect of the methods, the energy system of a high-rise building is introduced. The design on the chilled water pump system and cooling towers is improved. The control strategies for chillers,pumps and fresh air systems are optimized. The energy saving and cost from the design and control optimization methods are analyzed. The presented methodology will provide users and stakeholders an effective approach to improve the energy efficiency of building energy systems and promote the development of smart buildings and smart cities.

Aseismic smart building isolation systems under multi-level earthquake excitations： Part I, conceptual design and nonlinear analysis

As a novel structural control strategy, tuned mass damper （TMD） inspired passive and semi-active smart building isolation systems are suggested to reduce structural response and thus mitigate structural damage due to earthquake excitations. The isolated structure＇s upper stories can be utilized as a large scaled TMD, and the isolation layer, as a core design point, between the separated upper and lower stories entails the insertion of rubber bearings and （i） viscous dampers （passive） or （ii） resettable devices （semi-active）. The seismic performance of the suggested isolation systems are investigated for 12-story reinforced concrete moment resisting flames modeled as ＂10 ~ 2＂ stories and ＂8 ＋ 4＂ stories. Passive viscous damper or semi-active resettable devices are parametrically evaluated through the optimal design principle of a large mass ratio TMD. Statistical performance metrics are presented for 30 earthquake records from the three suites of the SAC project. Based on nonlinear structural models, including P-delta effects and modified Takeda hysteresis, the inelastic time history analyses are conducted to compute the seismic performances across a wide range of seismic hazard intensities. Results show that semi-active smart building isolation systems can effectively manage seismic response for multi-degree-of freedom （MDOF） systems across a broader range of ground motions in comparison to uncontrolled case and passive solution.

Secure Multifactor Remote Access User Authentication Framework for IoT Networks

The term IoT refers to the interconnection and exchange of data among devices/sensors.IoT devices are often small,low cost,and have limited resources.The IoT issues and challenges are growing increasingly.Security and privacy issues are among the most important concerns in IoT applications,such as smart buildings.Remote cybersecurity attacks are the attacks which do not require physical access to the IoT networks,where the attacker can remotely access and communicate with the IoT devices through a wireless communication channel.Thus,remote cybersecurity attacks are a significant threat.Emerging applications in smart environments such as smart buildings require remote access for both users and resources.Since the user/building communication channel is insecure,a lightweight and secure authentication protocol is required.In this paper,we propose a new secure remote user mutual authentication protocol based on transitory identities and multi-factor authentication for IoT smart building environment.The protocol ensures that only legitimate users can authenticate with smart building controllers in an anonymous,unlinkable,and untraceable manner.The protocol also avoids clock synchronization problem and can resist quantum computing attacks.The security of the protocol is evaluated using two different methods:(1)informal analysis;(2)model check using the automated validation of internet security protocols and applications(AVISPA)toolkit.The communication overhead and computational cost of the proposed are analyzed.The security and performance analysis show that our protocol is secure and efficient.

Physical-data Fusion Modeling Method for Energy Consumption Analysis of Smart Building

The energy consumption of buildings accounts for approximately 40%of total energy consumption.An accurate energy consumption analysis of buildings can not only promise significant energy savings but also help estimate the demand response potential more accurately,and consequently brings benefits to the upstream power grid.This paper proposes a novel physical-data fusion modeling(PFM)method for modeling smart buildings that can accurately assess energy consumption.First,a thermal process model of buildings and an electrical load model that focus on building heating,ventilation,and air conditioning(HVAC)systems are presented to analyze the thermal-electrical conversion process of energy consumption of buildings.Second,the PFM method is used to improve the accuracy of the energy consumption analysis model for buildings by modifying the parameters that are difficult to measure in the physical model(i.e.,it effectively modifies the electrical load model based on the proposed PFM method).Finally,case studies involving a real-world dataset recorded in a high-tech park in Changzhou,China,demonstrate that the proposed method exhibits superior performance with respect to the traditional physical modeling(TPM)method and data-driven modeling(DDM)method in terms of the achieved accuracy.

A review on 5G technology for smart energy management and smart buildings in Singapore

Sustainable and smart building is a recent concept that is gaining momentum in public opinion,and thus,it is making its way into the agendas of researchers and city authorities all over the world.To move towards sustainable development goals,5G technology would make significant impacts are building construction,operation,and management by facilitating high-class services,providing efficient functionalities.It’s well known that the Singapore is one of top smart cities in this world and from the first counties that adopted of 5G technology in various sectors including smart buildings.Based on these facts,this paper discusses the international trends in 5G applications for smart buildings,and R&D and test bedding works conducted in 5G labs.As well as,the manuscript widely reviewed and discussed the 5G technology development,use cases,applications and future projects which supported by Singapore government.Finally,the 5G use cases for smart buildings and build environment improvement application were discussed.This study can serve as a benchmark for researchers and industries for the future progress and development of smart cities in the context of big data.

Nanotechnology as a Sustainable Approach for Achieving Sustainable Future

The nanotechnology revolution affected positively Architecture. Using nanotechnology is considered one of the most successful modern methods to achieve sustainable buildings with high functional efficiency. The discipline is Nano architecture, which uses Nanomaterials, products, or even Nano-shapes in the treatment of structure and construction. Despite the economic and urban advantages of using nanotechnology in the field of architecture and urbanism, we note that using nanotechnology is limited to some buildings uses in the city centers until now such as Administrative, commercial, educational, health, and recreational buildings or residential buildings. In spite of that, we found that nanotechnology was not used in priority buildings as “nuclear power plants” as it is considered one of the most eligible buildings to rely on nanotechnology to achieve safety, security, and functional efficiency requirements which have a great impact on advancing the movement of urban development. From this standpoint, the research recommends the necessity of following a methodology to activate the establishment of nuclear power plants with such technology to preserve the safety of construction, reduce energy consumption, conserve economic resources and reduce pollution. The research is exposed to highlight a set of case studies that used such an effective technique and conclude a group of criteria that are recommended to be followed in the implementation and construction of the Dabaa plant in Egypt to achieve a sustainable nuclear power plant. So the research objective aims to adopt the idea of applying nanotechnology in various uses, whether it is in the city center or the outskirt of the city in order to develop these urban cities and transform them into smart sustainable environmental cities depending on nanotechnology aspects to achieve new sustainability scenario that accommodates the objectives of sustainability, with the support of new technologies. From this point of view, the research presents a proposal that includes a set of points that are recommended to be followed based on nanotechnology to achieve sustainability in the implementation of the Dabaa nuclear power plant in Egypt;which will have a great impact in advancing the movement of urban development in Egypt through improving the envelope of an urban typology, using nanotechnology materials on the façades, roofs, and external renovations with suitable constructive systems and in an easier way.

Hybrid-integer algorithm for a multi-objective optimal home energy management system

Most of the energy produced in the world is consumed by commercial and residential buildings.With the growth in the global economy and world demographics,this energy demand has become increasingly important.This has led to higher unit electricity prices,frequent stresses on the main electricity grid and carbon emissions due to inefficient energy management.This paper presents an energy-consumption management system based on time-shifting of loads according to the dynamic day-ahead electricity pricing.This simultaneously reduces the electricity bill and the peaks,while maintaining user comfort in terms of the operating waiting time of appliances.The proposed optimization problem is formulated mathematically in terms of multi-objective integer non-linear programming,which involves constraints and consumer preferences.For optimal scheduling,the management problem is solved using the hybridization of the particle swarm optimization algorithm and the branch-and-bound algorithm.Two techniques are proposed to manage the trade-off between the conflicting objectives.The first technique is the Pareto-optimal solutions classification using supervised learning methods.The second technique is called the lexicographic method.The simulations were performed based on residential building energy consumption,time-of-use pricing(TOU)and critical peak pricing(CPP).The algorithms were implemented in Python.The results of the current work show that the proposed approach is effective and can reduce the electricity bill and the peak-to-average ratio(PAR)by 28% and 49.32%,respectively,for the TOU tariff rate,and 48.91% and 47.87% for the CPP tariff rate by taking into account the consumer’s comfort level.

Application of CPS Under the Background of Intelligent Construction

The advent of the fourth industrial revolution(Industry 4.0)has brought about new opportunities for the intelligent transformation and upgrading of the construction industry to achieve high-quality and sustainable development.On the basis of analyzing the background of the industry and the development status of the corresponding technologies used in intelligent construction,the application of cyber-physical system(CPS)is proposed.The CPS intelligent construction platform is created in response to the demands of the construction industry’s current growth to provide digital solutions.The drawbacks and challenges in the current construction development process have aided in the industry’s transformation and upgrading.