Search Results (692)

Embedded systems in IoT are expected to be run by reliable, resource-efficient software. Devices on the edge are typically required to communicate with central nodes, and in some setups with each other, constituting a distributed system. The Erlang language, favored for its constructs that support building fault-tolerant, distributed systems, offers solutions to these challenges. Its dynamic type system and higher-level abstractions enable fast development, while also featuring tools for building highly available and fault-tolerant applications. To study the viability of using Erlang in embedded systems, we analyze the solutions the language offers, contrasting them with the challenges of developing embedded systems, with a particular focus on resource use. We measure the footprint of the language’s constructs in executing tasks characteristic of end devices, such as gathering, processing and transmitting sensor data. We conduct our experiments with constructs and data of varying sizes to account for the diversity in software complexity of real-world applications. Our measured data can serve as a basis for future research, supporting the design of the software stack for embedded systems. Our results demonstrate that Erlang is an ideal technology for implementing software on embedded systems and a suitable candidate for developing a prototype for a real-world use case. Full article

Evaluating the renewable energy potential, such as that of solar photovoltaics (PV), is important for developing renewable energy policies. This study investigated rooftop solar PV potential in Thailand based on open-source geographic information system (GIS) building footprints, solar PV power output, and the most recent land use data (2022). GIS-based overlay analysis, buffering, fishnet modeling, and spatial join operations were applied to assess rooftop availability across various building types, taking into account PV module installation parameters and optimal panel orientation. Economic feasibility and sensitivity analyses were conducted using standard economic metrics, including net present value (NPV), internal rate of return (IRR), payback period, and benefit–cost ratio (BCR). The findings showed a total rooftop solar PV power generation potential of 50.32 TWh/year, equivalent to 25.5% of Thailand’s total electricity demand in 2022. The Central region contributed the highest potential (19.59 TWh/year, 38.94%), followed by the Northeastern (10.49 TWh/year, 20.84%), Eastern (8.16 TWh/year, 16.22%), Northern (8.09 TWh/year, 16.09%), and Southern regions (3.99 TWh/year, 7.92%). Both commercial and industrial sectors reflect the financial viability of rooftop PV installations and significantly contribute to the overall energy output. These results demonstrate the importance of incorporating rooftop solar PV in renewable energy policy development in regions with similar data infrastructure, particularly the availability of detailed and standardized land use data for building type classification. Full article

Nanofluids are an innovative working medium in solar hot water installations (DHWs), thanks to their increased thermal conductivity and heat transfer coefficient. The aim of this work was to assess the effect of Al₂O₃ nanofluids in a water–ethylene glycol base (40:60%) and with the addition of Tween 80 surfactant (0.2 wt%) on thermal efficiency (ε) and exergy (η_ex) in a plate heat exchanger at DHW flows of 3 and 12 L/min. The numerical NTU–ε model was used with dynamic updating of thermophysical properties of nanofluids and the solution of the ODE system using the ode45 method, and the validation was carried out against the literature data. The results showed that the nanofluids achieved ε ≈ 0.85 (vs. ε ≈ 0.87 for the base fluid) and η_ex ≈ 0.72 (vs. η_ex ≈ 0.74), with higher entropy generation. The addition of Tween 80 reduced the viscosity by about 10–15%, resulting in a slight increase of Re and h-factor; however, the impact on ε and η_ex was marginal. The environmental analysis with an annual demand of Q = 3000 kWh/year and an emission factor of 0.2 kg CO₂/kWh showed that for ε < 0.87 the nanofluids increased the emissions by ≈16 kg CO₂/year, while at ε ≈ 0.92, a reduction of ≈5% was possible. This paper highlights the need to optimize nanofluid viscosity and exchanger geometry to maximize energy and environmental benefits. Nowadays, due to the growing problems of global warming, the analysis of energy efficiency and carbon footprint related to the functioning of a building seems to be crucial. Full article

Building height information plays an important role in many urban-related applications, such as urban planning, disaster management, and environmental studies. With the rapid development of real scene maps, street view images are becoming a new data source for building height estimation, considering their easy collection and low cost. However, existing studies on building height estimation primarily utilize remote sensing images, with little exploration of height estimation from street-view images. In this study, we proposed a deep learning-based method for estimating the height of a single building in Baidu panoramic street view imagery. Firstly, the Segment Anything Model was used to extract the region of interest image and location features of individual buildings from the panorama. Subsequently, a cross-view matching algorithm was proposed by combining Baidu panorama and building footprint data with height information to generate building height samples. Finally, a Two-Branch feature fusion model (TBFF) was constructed to combine building location features and visual features, enabling accurate height estimation for individual buildings. The experimental results showed that the TBFF model had the best performance, with an RMSE of 5.69 m, MAE of 3.97 m, and MAPE of 0.11. Compared with two state-of-the-art methods, the TBFF model exhibited robustness and higher accuracy. The Random Forest model had an RMSE of 11.83 m, MAE of 4.76 m, and MAPE of 0.32, and the Pano2Geo model had an RMSE of 10.51 m, MAE of 6.52 m, and MAPE of 0.22. The ablation analysis demonstrated that fusing building location and visual features can improve the accuracy of height estimation by 14.98% to 69.99%. Moreover, the accuracy of the proposed method meets the LOD1 level 3D modeling requirements defined by the OGC (height error ≤ 5 m), which can provide data support for urban research. Full article

Urban agriculture (UA) is emerging as a promising strategy for sustainable food production in response to growing environmental pressures. Indoor vertical farming (IVF), combining Controlled Environment Agriculture (CEA) with Building-Integrated Agriculture (BIA), enables efficient resource use and year-round crop cultivation in urban settings. This study assesses the environmental performance of a prospective IVF system located on a university campus in Portugal, focusing on the integration of photovoltaic (PV) energy as an alternative to the conventional electricity grid (GM). A Life Cycle Assessment (LCA) was conducted using the Environmental Footprint (EF) method and the LANCA model to account for land use and soil-related impacts. The PV-powered system demonstrated lower overall environmental impacts, with notable reductions across most impact categories, but important trade-offs with decreased soil quality. The LANCA results highlighted cultivation and packaging as key contributors to land occupation and transformation, while also revealing trade-offs associated with upstream material demands. By combining EF and LANCA, the study shows that IVF systems that are not soil-based can still impact soil quality indirectly. These findings contribute to a broader understanding of sustainability in urban farming and underscore the importance of multi-dimensional assessment approaches when evaluating emerging agricultural technologies. Full article

In the context of the growing need to reduce greenhouse gas emissions and to develop sustainable solutions for the construction industry, foamed geopolymers represent a promising alternative to traditional binders and insulation materials. This study investigates the thermal properties of novel low-emission, insulating geopolymer binders made from fly ash with diatomite, chalcedonite, and wood wool aiming to assess their potential for use in thermal insulation systems in energy-efficient buildings. The stability of the foamed geopolymer structure is also assessed. Measurements of thermal conductivity, specific heat, microstructure, density, and compressive strength are presented. The findings indicate that the selected geopolymer formulations exhibit low thermal conductivity, high heat capacity and low density, making them competitive with conventional insulation materials—mainly load-bearing ones such as aerated concrete and wood wool insulation boards. Additionally, incorporating waste-derived materials reduces the production carbon footprint. The best results are represented by the composite incorporating all three additives (diatomite, chalcedonite, and wood wool), which achieved the lowest thermal conductivity (0.10154 W/m·K), relatively low density (415 kg/m³), and high specific heat (1.529 kJ/kg·K). Full article

Rammed earth (RE), a traditional material aligned with circular economy (CE) principles, has been gaining renewed interest in contemporary construction due to its low environmental impact and compatibility with sustainable building strategies. Though not a modern invention, it is being reintroduced in response to the increasingly strict European Union (EU) regulations on carbon footprint, life cycle performance, and thermal efficiency. RE walls offer multiple benefits, including humidity regulation, thermal mass, plasticity, and structural strength. This study also draws attention to their often-overlooked ability to mitigate indoor overheating. To preserve these advantages while enhancing thermal performance, this study explores insulation strategies that maintain the vapor-permeable nature of RE walls. A parametric analysis using Delphin 6.1 software was conducted to simulate heat and moisture transfer in two main configurations: (a) a ventilated system insulated with mineral wool (MW), wood wool (WW), hemp shives (HS), and cellulose fiber (CF), protected by a jute mat wind barrier and finished with wooden cladding; (b) a closed system using MW and WW panels finished with lime plaster. In both cases, clay plaster was applied on the interior side. The results reveal distinct hygrothermal behavior among the insulation types and confirm the potential of natural, low-processed materials to support thermal comfort, moisture buffering, and the alignment with CE objectives in energy-efficient construction. Full article

As the construction industry continues to evolve, energy consumption of buildings, particularly CO₂ emissions, has become a critical focus for sustainable development. The need for effective design decisions regarding the selection of materials throughout the project life cycle is apparent, yet the link between specifications and CO₂ emissions has not been set yet. This study presents a comprehensive life cycle assessment (LCA) of CO₂ emissions across various Construction Specifications Institute (CSI) categories, aiming to identify the carbon footprint of different building systems and materials. The methodology focuses on using 3D building model case studies to evaluate the design decisions versus their impact on global warming potential (GWP). The results of this study emphasize that within CSI categories, concrete divisions consistently emerge as the predominant contributors to GWP, exceeding 75% in several instances. Following closely, metals contribute approximately 50% in multiple projects. The study also explores sustainable design options across CSI divisions to provide insights into building components contributing most to a building’s overall carbon footprint. This deeper understanding of sustainable design principles regarding CSI divisions and their impact on carbon footprint reduction will help sustainable designers and construction managers to implement carbon-conscious material choices and design strategies early in the planning phase. Full article

Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation. As a result, rapidly screening genetic libraries, exploring combinatorial designs, or optimizing electroporation parameters requires extensive iterations, consuming large quantities of expensive custom-made DNA and cell lines or primary cells. To address these limitations, we have developed a High-Throughput Microfluidic Electroporation (HTME) platform that includes a 384-well electroporation plate (E-Plate) and control electronics capable of rapidly electroporating all wells in under a minute with individual control of each well. Fabricated using scalable and cost-effective printed-circuit-board (PCB) technology, the E-Plate significantly reduces consumable costs and reagent consumption by operating on nano to microliter volumes. Furthermore, individually addressable wells facilitate rapid exploration of large sets of experimental conditions to optimize electroporation for different cell types and plasmid concentrations/types. Use of the standard 384-well footprint makes the platform easily integrable into automated workflows, thereby enabling end-to-end automation. We demonstrate transformation of E. coli with pUC19 to validate the HTME’s core functionality, achieving at least a single colony forming unit in more than 99% of wells and confirming the platform’s ability to rapidly perform hundreds of electroporations with customizable conditions. This work highlights the HTME’s potential to significantly accelerate synthetic biology Design-Build-Test-Learn (DBTL) cycles by mitigating the transformation/transfection bottleneck. Full article

With increasing electrification and the connection of more renewable resources at the transmission level, bulk interconnected electric grids need to plan network expansion with new transmission facilities. The transmission expansion planning (TEP) problem is particularly challenging because of the combinatorial, integer optimization nature of the problem and the complexity of engineering analysis for any one possible solution. Network synthesis methods, that is, heuristic-based techniques for building synthetic electric grid models based on complex network properties, have been developed in recent years and have the capability of balancing multiple aspects of power system design while efficiently considering large numbers of candidate lines to add. This paper presents a methodology toward scalability in addressing the large-scale TEP problem by applying network synthesis methods. The algorithm works using a novel heuristic method, inspired by simulated annealing, which alternates probabilistic removal and targeted addition, balancing the fixed cost of transmission investment with objectives of resilience via power flow contingency robustness. The methodology is demonstrated in a test case that expands a 2000-bus interconnected synthetic test case on the footprint of Texas with new transmission to support 2025-level load and generation. Full article

To respond to the challenge of global climate change, universities should engage in carbon footprint research to identify effective strategies for mitigating greenhouse gas emissions. In this research, a comprehensive framework tailored for the study of carbon footprints in universities was constructed and used in a university in Northeast China for a case study, based on the GHG Protocol and emission factor methodology. The sources of GHG emissions at this university were identified by the GHG Protocol. Activity data were collected through questionnaire surveys and field visits. The results show that the university’s annual carbon footprint in 2022 stands at 172,473.77 t CO₂-eq, with the contributions of Scope 1, 2, and 3 accounting for 2.35%, 64.69%, and 32.96%, respectively. Based on the carbon footprint quantification results, campus carbon reduction strategies were put forward from four perspectives: individual activities, building energy management, energy-loss reduction, and carbon sink, in order to enhance the sustainability of this university. An important difference between this work and previous studies is the explicit emphasis on the necessity of the indicative role of the carbon footprint in carbon reduction efforts. The case demonstrates the application of research framework and methods, providing methodologies and case references for future research on the carbon footprint of universities. Full article

The forming methodology influences the physicochemical, mechanical, and microstructural properties. In this study, which aims to develop a geopolymeric material for potential insulation applications in buildings such as vertical walls, geopolymers were developed using industrial wastes from different industries: slate stone cutting sludge (SSCS) and chamotte (CH) were used as precursors, and olive stone bottom ash (OSBA) and sodium silicate (Na₂SiO₃) were used as alkaline activators. Two forming methods were evaluated: uniaxial pressing and casting of the material, varying the forming method and the liquid/solid ratio. The results showed that the pressed geopolymers achieved higher bulk densities (up to 2.13 g/cm³) and significantly higher compressive strength (28.04 MPa at 28 days), attributable to a higher compactness and degree of geopolymer reaction. In contrast, the casting geopolymers exhibited surface efflorescence, related to slower curing and higher porosity, which reduced their compressive strength (17.88 MPa). In addition, the pressed geopolymers showed better thermal stability and fire performance. These results demonstrate that the variation of the forming method has a direct influence on the material properties of geopolymers, and that the pressing process allows for a reduction of the alkaline activator content, thus reducing its environmental footprint. Full article

Effective post-disaster damage assessment is crucial for guiding emergency response and resource allocation. This study introduces DamageScope, an integrated deep learning framework designed to detect and classify building damage levels from post-disaster satellite imagery. The proposed system leverages a convolutional neural network trained exclusively on post-event data to segment building footprints and assign them to one of four standardized damage categories: no damage, minor damage, major damage, and destroyed. The model achieves an average F1 score of 0.598 across all damage classes on the test dataset. To support geospatial analysis, the framework extracts the coordinates of damaged structures using embedded metadata, enabling rapid and precise mapping. These results are subsequently visualized through an interactive, web-based platform that facilitates spatial exploration of damage severity. By integrating classification, geolocation, and visualization, DamageScope provides a scalable and operationally relevant tool for disaster management agencies seeking to enhance situational awareness and expedite post-disaster decision making. Full article

Currently, the cement industry stands as one of the sectors with the most significant environmental impact, primarily due to its substantial greenhouse gas emissions and energy consumption. To mitigate this impact, a roadmap has been followed in recent years, outlining a set of objectives aimed at diminishing the environmental footprint of the construction industry. This research focuses on the development of mortars with different water/cement ratios employing an alternative cement, specifically magnesium phosphate cement (MPC) formulated with secondary sources. The goal of this research relays in developing mortars based on MPC by using waste from the metallurgical industry, named tundish deskulling waste (TUN), as an MgO source. The results revealed the optimal water/cement (W/C) ratio for MPC-TUN mortars production through the assessment of various characterization techniques, which was 0.55. This ratio resulted in the highest compressive strength after 28 days of curing and the formation of a stable K-struvite matrix. Furthermore, it demonstrated the effectiveness of aluminum sulphate in preventing efflorescence caused by carbonates. The development of alternative masonry mortars for application in building materials represents a significant stride towards advancing the principles of a circular economy, in alignment with the objectives laid out in the 2030 roadmap. Full article

The development of retail stores is determined by many factors, including the availability of retail space. The construction of a new building requires time, resources, and permits. This article aims to examine the possibilities of implementing small modular retail facilities built on the principles of vending machines, which do not require constant service and social space, by examining important groups of factors: architectural and structural, production, environmental, and costs. A vending machine in modular construction technology provides new opportunities for the development of a retail network in previously inaccessible places. The research presented in this article was conducted based on a literature review and interviews with experts, on the basis of which, using the network thinking methodology, critical factors were isolated and analysed in detail. The research results show the benefits of using modular technology, meeting the assumptions of the circular economy in terms of reducing the carbon footprint and improving the construction stage and investment costs, while taking into account the aesthetics of the surroundings. The results can contribute to the popularisation of the use of modular facilities, which can complement the development of downtown areas, making cities more sustainable. Full article