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This study aims to create an efficient approach to validate building energy simulation models amidst challenges from time-intensive data collection. Emphasizing precision in model calibration through strategic short-term data acquisition, the systematic framework targets critical adjustments using a strategically captured dataset. Leveraging metrics like Mean Bias Error (MBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)), this methodology aims to heighten energy efficiency assessment accuracy without lengthy data collection periods.

A standalone school and a campus facility were selected as case studies. Field investigations enabled precise energy modeling, emphasizing user-dependent parameters and compliance with standards. Simulation outputs were compared to short-term actual measurements, utilizing MBE and CV(RMSE) metrics, focusing on internal temperature and CO₂ levels. Energy bills and consumption data were scrutinized to verify natural gas and electricity usage against uncertain parameters.

Discrepancies between initial simulations and measurements were observed. Following adjustments, the standalone school 1’s average internal temperature increased from 19.5 °C to 21.3 °C, with MBE and CV(RMSE) aiding validation. Campus facilities exhibited complex variations, addressed by accounting for CO₂ levels and occupancy patterns, with similar metrics aiding validation. Revisions in lighting and electrical equipment schedules improved electricity consumption predictions. Verification of natural gas usage and monthly error rate calculations refined the simulation model.

This paper tackles Building Energy Simulation validation challenges due to data scarcity and time constraints. It proposes a strategic, short-term data collection method. It uses MBE and CV(RMSE) metrics for a comprehensive evaluation to ensure reliable energy efficiency predictions without extensive data collection.

Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.

The purpose of this paper is to present a strategic overview of the current literature on “Building information modelling (BIM) for Building Refurbishment and Maintenance” to unfold the factors behind the relative underdeveloped state of the field and to contribute to the development of a more cumulative knowledge base by presenting the current status and suggesting future directions for research.

A systematic review of the literature has been undertaken by classifying and mapping the literature, identifying the input-output relations, exhibiting the areas focused on by researchers as well as neglected ones and by indicating the trends in research through the years. Both qualitative and quantitative analysis is used in the study to better interpret the existing studies in a holistic perspective.

Although the need for BIM in facility management (FM) has been acknowledged by researchers and practitioners, the results highlight that studies related to BIM applications in maintenance and especially refurbishment are relatively recent. However, the trend in published articles shows that the interest is continuously growing. Existing research in this field can be clustered in the following subtopics: (1) building survey and as-built BIM, (2) modelling and managing energy, (3) design assessment, (4) access to and integration of maintenance information and knowledge, and (5) information exchange and interoperability.

The paper identifies the gaps in the research domain that hinders a widespread adoption of BIM in refurbishment and maintenance stages and introduces roadmaps to surmount the challenges identified in each specific subtopic of the field.

This article presents a case study on the Heritage Building Information Modeling (H-BIM) application in a historic village in Bursa, Turkey. The study addresses how tailor-made and highly structured H-BIM approaches can effectively be implemented in preservation applications for historic vernacular buildings in the rural architecture context.

Using inexpensive digital photogrammetry techniques tightly combined with an object-oriented BIM ontology, parametric meta-modeling and object/system propagation methods, the study employed a holistic H-BIM approach for capturing the materiality, building object behaviors and indigenous construction principles of a characteristic vernacular house that were synthesized in a parametric H-BIM model. The followed stages, steps and connected methods were systematized and articulated in a prototypical H-BIM implementation framework.

The study findings suggested that the developed parametric H-BIM approach can return effective results with the combined use of low-cost and practical digital photogrammetry with BIM methods. The flexibility and adaptability of the parametric H-BIM implementation framework facilitated the synthesis of a comprehensive H-BIM model and allowed an in-depth evaluation of local architectural heritage with its physical, spatial and environmental characteristics. The proposed H-BIM approach also provided significant documentation and system-specific assessment benefits for preserving the vernacular examples which are prone to extinction especially due to structural and systemic deterioration.

The study proposes a feasible, practical and replicable H-BIM implementation methodology for vernacular preservation applications. The knowledge-embedded H-BIM approach, flows and techniques presented in this study provide a holistic and systematic H-BIM framework – with the integrated use of digital photogrammetry and parametric meta-modeling methods – that has the potential for the democratization of H-BIM applications in education and practice.

The purpose of this paper is to present a review of the implications building information modelling (BIM) is having on the building energy modelling (BEM) and design of buildings. It addresses the issues surrounding exchange of information throughout the design process, and where BIM may be useful in contributing to effective design progression and information availability.

Through review of current design procedures and examination of the concurrency between architectural and thermophysical design modelling, a procedure for information generation relevant to design stakeholders is created, and applied to a high-performance building project currently under development.

The extents of information key to the successful design of a buildings energy performance in relation to its architectural objectives are given, with indication of the level of development required at each stage of the design process.

BIM offers an extensible medium for parametric information storage, and its implementation in design development offers the capability to include BEM parameter-integrated construction information. The extent of information required for accurate BEM at stages of a building’s design is key to understanding how best to record performance information in a BIM environment.

This paper contributes to the discussion around the integration of concurrent design procedures and a common data environment. It presents a framework for the creation and dissemination of information during design, exemplifies this on a real building project and evaluates the barriers experienced in successful implementation.

The rapid urbanization of Indian cities and the population surge in cities has steered a massive demand for energy, thereby increasing the carbon emissions in the environment. Information and technology advancements, aided by predictive tools, can optimize this energy demand and help reduce harmful carbon emissions. Out of the multiple factors governing the energy consumption and comfort of buildings, indoor room temperature is a critical one, as it envisages the need for regulating the temperature. This paper aims to propose a mathematical model for short-term forecasting of indoor room temperature in the Indian context to optimize energy consumption and reduce carbon emissions in the environment.

A study is conducted to forecast the indoor room temperature of an Indian corporate building structure, based upon various external environmental factors: temperature and rainfall and internal factors like cooling control, occupancy behavior and building characteristics. Expert insight and principal component analysis are applied for appropriate variables selection. The machine learning approach using Box–Jenkins time series models is used for the forecasting of indoor room temperature.

ARIMAX model, with lagged forecasted and explanatory variables, is found to be the best-fit model. A predictive short-term hourly temperature forecasting model is developed based upon ARIMAX model, which yields fairly accurate results for data set pertaining to the building conditions and climatic parameters in the Indian context. Results also investigate the relationships between the forecasted and individual explanatory variables, which are validated using theoretical proofs.

The models considered in this research are Box–Jenkins models, which are linear time series models. There are non-linear models, such as artificial neural network models and deep learning models, which can be a part of this study. The study of hybrid models including combined forecasting techniques comprising linear and non-linear methods is another important area for future scope of study. As this study is based on a single corporate entity, the models developed need to be tested further for robustness and reliability.

Forecasting of indoor room temperature provides essential practical information about meeting the in-future energy demand, that is, how much energy resources would be needed to maintain the equilibrium between energy consumption and building comfort. In addition, this forecast provides information about the prospective peak usage of air-conditioning controls within the building indoor control management system through a feedback control loop. The resultant model developed can be adopted for smart buildings within Indian context.

This study has been conducted in India, which has seen a rapid surge in population growth and urbanization. Being a developing country, India needs to channelize its energy needs judiciously by minimizing the energy wastage and reducing carbon emissions. This study proposes certain pre-emptive measures that help in minimizing the consumption of available energy resources as well as reducing carbon emissions that have significant impact on the society and environment at large.

A large number of factors affecting the indoor room temperature present a research challenge for model building. The paper statistically identifies the parameters influencing the indoor room temperature forecasting and their relationship with the forecasted model. Considering Indian climatic, geographical and building structure conditions, the paper presents a systematic mathematical model to forecast hourly indoor room temperature for next 120 h with fair degree of accuracy.

Three dimensional (3 D) laser scanner surveying is widely used in many fields, such as agriculture, mining and heritage documentation and can be of great benefit for as-built documentation in construction and facility management domains. However, there is lack of applied research and use cases integrating 3 D laser scanner surveying with building information modeling (BIM) for existing facilities in Malaysia. This study aims to develop a scan to as-built BIM workflow to use 3 D laser scanner surveying and create as-built building information models of an existing complex facility in Malaysia.

A case study approach was followed to develop a scan to as-built BIM workflow through four main steps: 3 D laser scanning, data preprocessing, data registration and building information modeling.

This case study proposes a comprehensive scan to as-built BIM workflow which illustrates all the required steps to create a precise 3 D as-built building information model from scans. This workflow was successfully implemented to the Eco-Home facility at the Universiti Teknologi Malaysia.

Scan to as-built BIM is a digital alternative to manual and tedious process of documentation of as-built condition of a facility and provides a detail process using laser scans to create as-built building information models of facilities.

The paper aims to investigate and evaluate the impacts of the voids combination as a passive design feature on wind-driven ventilation performance in high-rise residential building units. It proposes a series of building models and thereon indoor ventilation performance and outlining why and how these building models designed with architectural design features are important. This study aims to provide a comprehensive understanding of how natural ventilation as a passive cooling strategy in living units of high-rise residential buildings can be applied through improving the provision of the architectural design feature of voids configurations.

The study was carried out through field measurements experiment and the computational fluid dynamics methods. A series of numerical simulations were carried out to calculate the indoor ventilation rate inside the case studies of the generated building models based on various variables such as horizontal voids type, size and wind directions.

The results indicate that the provision of a single-sided horizontal voids in building models can improve the indoor ventilation rate in units with cross ventilation mode up to 4 times, depending on wind direction and living unit location. The indoor ventilation performance in units located in models with single-sided horizontal voids is 17.54% higher than the units located in models without voids configuration. Furthermore, higher indoor ventilation performance was achieved in the case scenarios located at higher levels compared to the middle and lower levels in both horizontal voids types.

This study explores the application of voids combinations for natural ventilation performance, investigates the numerical simulation results and validates field measurements experiment data using CFD simulation.

The purpose of this research is to investigate a new approach with its supporting building information modelling (BIM) + augmented reality (AR) tool to enhance architectural visualisation in building life cycle. Traditional approaches to visualise architectural design concentrate on static pictures or three-dimensional (3D) scale models which cause problems, such as expensive design evolution, lack of stakeholders’ communication and limited reusability. The 3D animated fly-throughs still occur on a computer screen in two-dimensions and seem cold and mechanical, unless done with advanced production software.

The method of this research included case study and interview. It was, first, stated, from the building process perspective, how the BIM + AR for Architectural Visualisation System (BAAVS) was realised by integrating two types of visualisation techniques: BIM and AR, and four stages of building life cycle. Then the paper demonstrated four case studies to validate the BAAVS. Finally, four interviews were made with each case manager and team members to collect feedback on utilising BAAVS technology. Questions were asked in the areas of benefits, drawbacks and technical limitations with respect to BAAVS.

Feedback from the stakeholders involved in the four cases indicated that BAAVS was useful and efficient to visualise architectural design and communicate with each other.

This paper demonstrates BAAVS that integrated BIM and AR into architectural visualisation. The system supports an innovative performance that allows: designers to put virtual building scheme in physical environment; owners to gain an immersive and interactive experience; and property sellers to communicate with customers efficiently.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.