21,240 Results Found

At present, the construction industry has not yet fully optimized the integration of the potential of big data. Past studies signaled the potential benefits of integrating building information management (BIM) and big data in the field of sustainable...

This study aims to propose a method for constructing basic digital twin data in South Korea by adhering to international standards and by utilizing publicly available data. Specifically, the study focuses on designing and proposing a digital twin dat...

The building sector is undergoing a deep transformation to contribute to meeting the climate neutrality goals set by policymakers worldwide. This process entails the transition towards smart energy-aware buildings that have lower consumptions and bet...

Building energy consumption prediction has a significant effect on energy control, design optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID-19 in buildings, providing a guarantee for energy efficiency and c...

The interoperability challenge is a long-standing challenge in the domain of architecture, engineering and construction (AEC). Diverse approaches have already been presented for addressing this challenge. This article will look into the possibility o...

Europe has set a target to become a decarbonised continent by 2050. To achieve this, intervention in buildings is crucial, as they serve as significant energy consumers and greenhouse gas emitters. This intervention encompasses two essential pathways...

This study investigated the effect of the building data knowledge level on seismic risk estimation for municipal building stocks, focusing on identifying the characteristics that influence loss estimation bias. Fifteen municipalities in two Slovenian...

Building fire is a complex geographic process related to the indoor spatial environment, a smart spatial data model can accurately describe the spatial-temporal information of a building fire scene, which is important for modeling a fire process. Wit...

The building permission process is to a large extent an analogue process where much information is handled in paper format or as pdf files. With the ongoing digitalisation in society, there is a potential to automate this process by integrating Build...

In an era where buildings are increasingly becoming multifaceted entities, the paradigm of smart buildings has witnessed significant evolution. This advancement integrates sophisticated communication technologies, the Internet of Things (IoT), artifi...

Data visualization has become relevant in the framework of the evolution of big data analysis. Being able to understand data collected in a dynamic, interactive, and personalized way allows for better decisions to be made when optimizing and improvin...

Buildings account for a majority of the primary energy consumption of the human society, therefore, analyses of building energy consumption monitoring data are of significance to the discovery of anomalous energy usage patterns, saving of building ut...

Internet of things (IoT) and big data technologies are increasingly gaining significance in the implementation of various services and applications. Consequently, much of the research focused on energy efficiency and building management revolves arou...

Building type information is widely used in various fields, such as disaster management, urbanization studies, and population modelling. Few studies have been conducted on fine-grained building classification in rural areas using China’s Gaofen...

The European Commission has mandated the use of digital building logbooks (DBL) to encourage deep energy renovations and overcome barriers in building renovations. The current energy performance certificates (EPCs) focus on operational energy consump...

The AEC industries as well as the heritage sector are facing a number of issues that relate to the management of building digital data. Two of the most prominent ones are the interoperability of data and data longevity. In order to better understand...

The construction industry is recognized as a major cause of environmental pollution, and it is important to quantify and evaluate building energy. As interest in big data has increased over the past 20 years, research using big data is active. Howeve...

Building energy simulation models have been used to assist the design and/or optimization of buildings energy performance. The results from building energy simulation models can be more reliable when measured energy use data, indoor environmental con...

Periodic building change detection is important for many applications, including disaster management. Building map databases need to be updated based on detected changes so as to ensure their currency and usefulness. This paper first presents a graph...

University building energy consumption is an important proportion of the total energy consumption of society. In order to work out the problem of poor practicability of the existing benchmarking management method of campus building energy consumption...

The extraction of skeleton lines of buildings is a key step in building spatial analysis, which is widely performed for building matching and updating. Several methods for vector data skeleton line extraction have been established, including the impr...

The demand for compact housing is on the rise, driven by the need for floor plans that accommodate stakeholders’ preferences. However, clients frequently struggle to convey their spatial needs to professionals, such as architects, due to a lack...

Smart management of urban built environment relies on the availability of data supporting sound policy making and guiding city renovation processes toward more sustainable and performant models. Nevertheless, public managers are unlikely to have comp...

Energy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop...

Advances in machine learning and computer vision, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics, cost-effectively, and at scale. These cha...

The development of data-driven building energy consumption prediction models has gained more attention in research due to its relevance for energy planning and conservation. However, many studies have conducted the inappropriate application of data-d...

This study investigates the feasibility and benefits of transferring data between Autodesk Revit (used for building information modeling (BIM)) and BUILDER SMS (used for sustainable facility management (SFM)). Two data transfer methods were evaluated...

Building change detection is useful for land management, disaster assessment, illegal building identification, urban growth monitoring, and geographic information database updating. This study proposes an automatic method that applies object-based an...

With increasing access to open spatial data, it is possible to improve the quality of analyses carried out in the preliminary stages of the investment process. The extraction of buildings from raster data is an important process, especially for urban...

The Retabit platform is a data-driven tool designed to bridge the gap between building rehabilitation and urban regeneration by integrating energy, economic, and social dimensions into a single framework. Leveraging multiple public data sources, the...

The need to improve the performance of Nigeria’s office buildings is due to, energy challenges, increasing population, changing user needs, and climate change. With the expansion of several Nigerian cities, existing buildings constitute a signi...

Digital twins are increasingly gaining popularity as a method for simulating intricate natural and urban environments, with the precise segmentation of 3D objects playing an important role. This study focuses on developing a methodology for extractin...

The architectural, engineering, construction, and operation (AECO) sector is one of the main contributors to energy consumption and greenhouse gas emissions in Europe, making the renovation of the existing building stock a priority. However, defining...

Three-dimensional building extraction is crucial for urban planning, environmental analysis, and autonomous navigation. One method for data collection involves using unmanned aerial vehicles (UAVs), which allow for flexible and rapid data acquisition...

Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important. There ar...

This study investigates the data integration of IoT-enabled sensor networks, emphasizing energy performance and personalized indoor air quality (IAQ) solutions to improve indoor environments, energy efficiency, and sustainability. Ontologies—st...

We compare different matching methods for distinguishing building modifications from replacements based on multi-temporal building footprint geometries from 3D city models. Manually referenced footprints of building changes were used to determine whi...

With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research e...

Assessing the seismic vulnerability of large numbers of buildings is an expensive and time-consuming task, requiring the collection of highly complex and multifaceted data on building characteristics and the use of sophisticated computational models....

OpenStreetMap (OSM) is a free map that can be created, edited, and updated by volunteers globally. The quality of OSM datasets is therefore of great concern. Extensive studies have focused on assessing the completeness (a quality measure) of OSM data...

Building Management Systems can be used for effective monitoring, management, planning, and improving the quality of work on large objects (office buildings, factories). Moreover, these systems can reduce costs during the operational phase. One of th...

Although the energy and cost benefits for retrofitting existing buildings are promising, several challenges remain for accurate measurement and verification (M&V) analysis to estimate these benefits. Due to the rapid development in advanced meter...

The renovation/modernisation of buildings is one of the most frequently addressed areas in the European Union. It is the basis for the entry into force of Directive 2010/31/EU on the energy performance of buildings. The assessment of renovated buildi...

In smart buildings, many different systems work in coordination to accomplish their tasks. In this process, the sensors associated with these systems collect large amounts of data generated in a streaming fashion, which is prone to concept drift. Suc...

An objective measure of building energy performance is crucial for performance assessment and rational decision making on energy retrofits and policies of existing buildings. One of the most popular measures of building energy performance benchmarkin...

In order to reduce the contribution of the building sector to global greenhouse gas emissions and climate change, it is important to improve the building performance through retrofits from the perspective of carbon emission reductions. Data-driven me...

The information of building types is highly needed for urban planning and management, especially in high resolution building modeling in which buildings are the basic spatial unit. However, in many parts of the world, this information is still missin...

Advances in metering technologies and emerging energy forecast strategies provide opportunities and challenges for predicting both short and long-term building energy usage. Machine learning is an important energy prediction technique, and is signifi...

Accurate modelling of occupancy patterns is critical for reliable estimation of building stock energy demand, which is a key input for the design of district energy systems. Aiming to investigate the suitability of different occupancy-modelling appro...

The successful construction of tall buildings requires effective construction management based on various quantitative data. The recent development of ubiquitous sensor networks (USNs) enables massive amounts of data to be collected in real-time. How...