Search Results (2,530)

Polystyrene is renowned for its excellent thermal insulation due to its closed-cell structure that traps air and reduces heat conduction. This study aims to develop sustainable, energy-efficient building materials by enhancing the thermal and mechanical properties of plaster–polystyrene bio-composites. By incorporating varying amounts of polystyrene (5% to 25%) into plaster, our research investigates changes in thermal conductivity, thermal resistance, and mechanical properties such as Young’s modulus and maximum stress. Meticulous preparation of composite samples ensures consistency, with thermal and mechanical properties assessed using a thermal chamber and four-point bending and tensile tests. The results show that increasing the polystyrene content significantly improved thermal insulation and stiffness, though maximum stress decreased, indicating a trade-off between insulation and mechanical strength. Full article

Energy consumption is indeed a significant challenge in many countries. It is important to promote sustainable practices for energy and resource conservation for future generations. Sustainable practices may be developed through architectural standards. Therefore, the aim of this study is to investigate the effects of architectural standards on energy consumption, especially in high-rise residential buildings located in Northern Iraq. To meet our aim, we collected primary data through a survey of five high-rise residential buildings that had different architectural standards located in Northern Iraq. Smart PLS-SEM was used for data analysis to obtain the results of the investigation. Our findings show that all the architecture standards, such as residential building envelope design, residential building system and control, residential building shape and massing, green roof and facade design, ventilation and natural ventilation, orientation and solar gain, and thermal comfort and insulation, have positive impacts on energy consumption, indicating the selected high-rise residential building have not followed the international standard in Iraq and have high energy consumption that is not cost-effective. Moreover, window design has a significant negative impact on energy consumption, indicating low energy consumption due to attractive and international standard window design. This study has significant implications for government, policy makers, architects, engineers, and stakeholders. Full article

The modern construction industry is undergoing considerable changes driven by increased specialization, technological advancements, and growing complexity. The integration of smart construction technology is rapidly advancing as a solution to address the aging workforce in the sector. However, the uncertainty and risks associated with soil construction on job sites remain, leading to increased costs during project execution. Recently, construction sites have sought to enhance productivity by leveraging building information modeling (BIM) and smart construction devices. The adoption of smart equipment, such as machine control and machine guidance, is on the rise in both structural and earthwork projects, with ongoing efforts to mitigate uncertainties. This study proposes a practical approach to reduce the uncertainty in earthworks by optimizing soil sharing strategies and equipment allocation from the initial design phase. A BIM model was developed as a solid structure and then segmented using Dynamo. This model was utilized to create a construction plan using Primavera P6, while AnyLogic (8.9.2) was employed to assess the suitability of equipment combinations, ultimately demonstrating the cost-saving benefits of the proposed approach. Through repeated simulations, work efficiency was enhanced by approximately 6.2% compared to the original 2D planning approach. Full article

The stability and reliability of a smart grid are challenged by the inherent intermittency and unpredictability of renewable energy as its integration into the smart grid increases. This places enormous pressure on the smart grid to manage high loads and volatility. To effectively mitigate the impact of new energy integration on smart grids, demand response (DR) can be altered to the demand-side burdens. Using residential smart buildings (RSBs) in Shanghai, this study proposes a carbon-aware demand response (CADR) model that is predicated on the coordination of power carbon intensity and real-time electricity prices. In order to accomplish a more comprehensive reduction in overall electricity consumption costs, we conducted real-time scheduling of a building’s electrical devices using a greedy algorithm. In addition, a model of an optimal charging and discharging scheme for household electric vehicles was established, which is based on various charging modes, taking into account the electrification of the transportation sector. The cost of EV charging is reduced by an average of 23.18% and 33.2% under the two common charging modes, while the integrated cost of the total annual electricity consumption of household devices is reduced by 8.69%, as indicated by the simulation results. Full article

As Internet of Things (IoT) technology continues to advance, there is a growing awareness of IoT security within the industry. Quantum communication technology can potentially significantly improve the communication security of IoT devices. Based on semi-quantum cryptography and utilizing single photons, this paper introduces two semi-quantum secure direct communication (SQSDC) protocols for use in smart door locks. Protocol 1 is more efficient, and the efficiency analysis shows that the communication efficiency is as high as 28.57%. Security analysis demonstrates the asymptotic security of the protocols, effectively resisting intercept–measure–resend attacks and entangle–measure attacks from potential eavesdroppers. The extended SQSDC protocol (protocol 2) builds upon protocol 1 by enabling a single qubit to transmit two bits of information, resulting in a double efficiency outcome. Full article

Hospitals use their websites to reinforce their relationships with stakeholders and build the brand collectively; however, they face challenges such as patients’ new needs or strict legal frameworks. This paper analyzes how Australia’s best hospitals manage their websites to implement content strategies that help them build their brands collectively with stakeholders. We conducted a literature review about smart hospitals, their corporate communication initiatives, and their online content strategies. Then, we identified 40 brand indicators to analyze how Australia’s best hospitals used their websites to interact with healthcare professionals, patients, media companies, and shareholders. We proved that most hospitals had sections for these targets (healthcare professionals -72.06%-, patients -85.51%-, media companies -98.53%, shareholders 100%-); however, they only respected, on average, 14.06 brand indicators. We concluded that Australian hospitals should follow a more emotional communication approach, make their brands more present on their website, and increase their collaborations with media companies. Full article

The working environment of the coal mine boom-type roadheader is harsh with large blind areas and numerous safety hazards for operators. Traditional on-site or remote control methods do not meet the requirements for intelligent tunneling. This paper proposes a digital twin monitoring system of an EBZ-type roadheader based on mixed reality (MR). First, the system integrates a five-dimensional digital twin model to establish the boom-type roadheader digital twin monitoring system. Second, the Unity3D software (v2020.3.25f1c1) and the MR Hololens (v22621.1133 produced by Microsoft) are used to build a digital twin human–machine interaction platform, achieving bidirectional mapping and driving of cutting operation data. Third, a twin data exchange program is designed by employing the Winform framework and the C/S communication architecture, making use of the socket communication protocol to transmit and store the cutting model data within the system. Finally, a physical prototype of the boom-type roadheader is built, and a validation experiment of the monitoring system’s digital twin is conducted. The experimental results show that the average transmission error of the cutting model data of the twin monitoring system is below 0.757%, and the execution accuracy error is below 3.7%. This system can achieve bidirectional real-time mapping and control between the twins, which provides a new monitoring method for actual underground roadheader operations. It effectively eliminates the operator’s blind areas and improves the intelligence level of roadheader monitoring. Beyond mining, this methodology can be extended to the monitoring and control of other mining equipment, predictive maintenance in manufacturing, and infrastructure management in smart cities. Full article

The development of information technologies has been exponentially applied to the architecture, engineering, and construction (AEC) industries. The extent of the literature reveals that the two most pertinent technologies are building information modeling (BIM) and artificial intelligence (AI) technologies. The radical digitization of the AEC industry, enabled by BIM and AI, has contributed to the emergence of “smart cities”, which uses information technology to improve urban operational and sustainable efficiency. Few studies have investigated the roles of AI and BIM in AEC from the perspective of sustainable buildings in assisting designers to make sustainable decisions at building and city levels. Therefore, the purpose of this paper is to explore the research status and future development trends in the relationship between AI and BIM-aided sustainable building in the context of the smart city to provide researchers, designers, and technology developers with potential research directions. This paper adopted a macro and micro bibliographic method, which is used to map out the general research landscape. This is followed by a more in-depth analysis of the fields of sustainable design, sustainable construction, sustainable development, and life cycle assessment (LCA). The results show that the combination of AI and BIM helps to make optimal decisions on materials, cost, energy, construction scheduling, and monitoring and promotes the development of sustainable buildings in both technical and human aspects so to achieve Sustainable Development Goals 7 (ensuring access to affordable, reliable, and sustainable modern energy for all), 9 (building resilient infrastructure, promote inclusive and sustainable industries, and foster innovation), 11 (building inclusive, safe, risk-resilient, and sustainable cities and human settlements), and 12 (ensuring sustainable consumption and production patterns). In addition, the combination of AI, BIM, and LCA technologies offers great potential to improve building performance, and the future development of AI and BIM integration should not only consider the sustainability of buildings but also consider the human-centered design concept and the health, safety, and comfort of stakeholders as one of the goals to realize the multidimensional development of smart city based on city information model. Full article

This paper examines Connected Smart Green Townhouses (CSGTs) as a modern residential building model in Burnaby, British Columbia (BC). This model incorporates a wide range of sustainable materials and smart components such as recycled insulation, Photovoltaic (PV) solar panels, smart meters, and high-efficiency systems. The CSGTs operate in grid-connected mode to balance on-site renewables with grid resources to improve efficiency, cost-effectiveness, and sustainability. Real datasets are used to optimize resource consumption, including electricity, gas, and water. Renewable Energy Sources (RESs), such as PV systems, are integrated with smart grid technology. This creates an effective framework for managing energy consumption. The accuracy, efficiency, emissions, and cost are metrics used to evaluate CSGT performance. CSGTs with one to four bedrooms are investigated considering water systems and party walls. A deep Machine Learning (ML) model combining Long Short-Term Memory (LSTM) and a Convolutional Neural Network (CNN) is proposed to improve the performance. In particular, the Mean Absolute Percentage Error (MAPE) is below 5%, the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) are within acceptable levels, and $R^2$ is consistently above 0.85. The proposed model outperforms other models such as Linear Regression (LR), CNN, LSTM, Random Forest (RF), and Gradient Boosting (GB) for all bedroom configurations. Full article

This research focuses on developing a low-cost automated demand response controller (DRC) with OpenADR 2.0a capability to enable existing infrared-controlled (IR-controlled) air conditioners (ACs) in homes and buildings to participate in automated demand response programs (ADRPs). The DRC consists of four modules: a smart socket module, an infrared module, a temperature sensor, and a voltage/current module. It can receive, analyze, and respond to demand response (DR) events and perform necessary demand and energy control strategies via IR. Power line communication (PLC) is used for communication without additional wiring. The system is tested under two conditions: participating in ADRPs via OpenADR and not participating in ADRPs. An 8.8% load reduction is observed with different temperature settings when not participating in ADRPs, and energy reductions of 21% to 46% are achieved using various cooling/fanning duty cycles in ADRPs. The proposed system can be integrated with any DR algorithm to meet demand management requirements under the OpenADR program, contributing to significant demand reductions. Full article

The detection of human activities is an important step in automated systems to understand the context of given situations. It can be useful for applications like healthcare monitoring, smart homes, and energy management systems for buildings. To achieve this, a sufficient data basis is required. The presented dataset contains labeled recordings of 25 different activities of daily living performed individually by 14 participants. The data were captured by five multisensors in supervised sessions in which a participant repeated each activity several times. Flawed recordings were removed, and the different data types were synchronized to provide multi-modal data for each activity instance. Apart from this, the data are presented in raw form, and no further filtering was performed. The dataset comprises ambient audio and vibration, as well as infrared array data, light color and environmental measurements. Overall, 8615 activity instances are included, each captured by the five multisensor devices. These multi-modal and multi-channel data allow various machine learning approaches to the recognition of human activities, for example, federated learning and sensor fusion. Full article

The construction of smart cities is an effective path for sustainable urban development. Determining how to build smart cities and choose effective development models has attracted attention from all walks of life. Consequently, determining how to promote the development of smart cities and how to choose effective development models has also attracted attention. This paper takes 77 prefecture-level cities in China as case studies to explore the impact of technology, organization, and environment on the high-level development of smart cities. In this study, the fsQCA (fuzzy set-based qualitative comparative analysis) method was used to explore the configuration effects of three types of factors. The main findings are as follows: Firstly, no single factor among the three categories is a necessary condition for the high development level of smart cities, indicating that relying solely on technological conditions cannot build high-level smart cities. Secondly, the path of development of a smart city can be summarized into three modes: Both organizational and industrial environment type, both governance and cultural environment type, and balanced development type. Finally, among the three modes, the government’s digital governance capability and industrial environment play a crucial role in achieving a high level of development in smart cities. This article examines the development of smart cities from a systems perspective and provides useful, practical insights for the construction of smart cities. Full article

In the past decade, 4D printing has received attention in the aerospace, automotive, robotics, and biomedical fields due to its lightweight structure and high productivity. Combining stimulus-responsive materials with 3D printing technology, which enables controllable changes in shape and mechanical properties, is a new technology for building smart bearing structures. A multilayer smart truss structural component with self-sensing function is designed, and an internal stress calibration strategy is established to better adapt to asymmetric loads. A material system consisting of continuous carbon fibers and polylactic acid was constructed, and an isosceles trapezoidal structure was chosen as the basic configuration of the smart component. The self-inductive properties are described by analyzing the relationship between the pressure applied to the specimen and the change in the specimen’s own resistance. Load-carrying capacity is realized by electrically heating the continuous carbon fibers in the component. Thermal deformation calibrates internal stress and enhances the load-carrying ability of the component over 50%. The experimental results demonstrate that the truss structure designed in this paper has strong self-induction, self-driving ability, and asymmetric load adaptation ability at the same time. This verifies that the 4D-printed smart component can be used as a load-carrying element, which broadens the application scope of smart components. Full article

Frequency-Selective Surfaces (FSSs) are structures that act as frequency-dependent electromagnetic filters, enabling innovative designs for energy-efficient building envelopes. This paper explores their potential for energy harvesting and integration into construction materials, offering insights into design strategies, performance analysis, and potential applications of FSS sin future architectural projects. A range of FSS designs are presented and systematically classified based on their performance and adaptability for building integration. This includes their use as part of traditional construction elements or as independent components of building walls. Critical issues such as the limitations, challenges, and durability of FSSs in real-world applications are also examined to provide a comprehensive view of their practical feasibility. Additionally, incorporating the electromagnetic properties of these materials into Building Information Modelling (BIM) systems is recommended. Doing so will enable architects and engineers to better utilize the novel opportunities that FSSs offer, fostering more innovative, energy-efficient building envelopes. Overall, this paper provides valuable insights into how FSSs can transform the future of sustainable architecture and energy management in buildings. Full article

Background/Objectives: Improved global data allow for a new understanding of what impact the food we produce, eat and dispose of has on the environment, human health and Nature’s resources. The overall goal is to guide decision-makers and individuals by providing in-depth knowledge about the effects of their dietary preferences on human and environmental health. Methods: The method is to investigate ways to reduce environmental degradation and to secure healthy food supplies in an urbanizing world, and to quantify the options. Results: Reviewed articles show that by eating less meat-based food and more plant-based and soilless food, as well as reducing food waste and recycling urban-disposed nutrients as fertilizers, we could reduce agriculture’s land requirement by 50% to 70% while still securing a healthy food supply. Less land under cultivation and pasture would reduce global emissions to air and water to a similar extent, and allow Nature to reclaim freed areas in order to catch more carbon and rejuvenate biodiversity. Thus, we could avoid further environmental degradation such as the current clearing of new fields needed under a business-as-usual regime. Presently, some 17 million people die each year due to poor diets, which is more than double the 7 million deaths since the onset of the COVID-19 pandemic. A return to more plant-based diets with unchanged intake of proteins but less calories, sugar, salt and fat combined with less red meat and ultra-processed food would reduce foremost non-communicable diseases by up to 20% and prolong life. The article suggests that the international focus has gradually turned to the food sector’s big contribution to climate change, biodiversity loss and harmful chemicals as well as to poor human health. It argues that this century’s rapid population growth and urbanization give urban residents a pivotal role in food’s impact on agricultural areas, which today cover half of the globe’s inhabitable areas. Their food demand, rather than the activities of farmers, fishermen or loggers, will guide remedial measures to be taken by individuals, industry and the public sector. A tool to calculate the potential environmental footprints of individual or societal measures is presented. Conclusions: Measures to make the agrifood sector more sustainable are still pending full recognition in international fora such as the UN COP Summits. Smart cities fitted with infrastructures to recycle macro- and micro-nutrients and organic matter have the potential to ameliorate human-induced impacts such as emissions to air and water bodies, crossing planetary boundaries, and polluting extraction of N (nitrogen), P (phosphorus) and K (potassium). Rapid results are within reach since dietary change and the turn-around time of nutrients in food is short compared to decades or centuries for recycled materials in cars or buildings. Full article