Automatic generation of building information models from digitized plans

This paper proposes a new approach to creating Building Information (BIM) models of existing buildings from digitized images. This automatic approach is based on three main steps. The first involves extracting the useful information automatically from rasterized plans by using image processing techniques that include segmentation, filtering, dilation, erosion, and contour detection. This information feeds the knowledge base of an expert system for BIM model generation. In the second step, using the knowledge base of the expert system, the information required to inform the BIM model can be deduced. The range of information thus obtainable can be extended beyond the examples given. The paper concludes with a discussion of the final stage: the automatic generation of an Industry Foundation Classes (IFC) information model with all the desired geometric, physical and technical information. This can be accomplished by using one of the available open-source application program interfaces (APIs). This stage is currently work-in-progress and will be the subject of a future publication

Assessing the influence of long-term urban growth scenarios on urban climate

International audienceThe objective of this paper is to assess the influence of future urban The objective of this paper is to assess the influence of future urban growth scenarios on future urban climate in Toulouse metropolitan area (France). Specifically, we aim to test the hypothesis that urban growth based on sprawling patterns has a significant influence on the Urban Heat Island (UHI) phenomena than compact patterns. Urban growth simulations, which are based on three contrasting scenarios built by 2100 with respect to different urban patterns, are made using a new spatially explicit urban growth model (SLEUTHR) which is specifically developed for that purpose. Potential UHI maps of 2006 and by 2100 are estimated under the same climate conditions using the SURFEX climate model. The influence of urban form on urban microclimate is assessed by comparing the estimated UHI map of 2006 with the potential UHI maps expected by 2100 with respect to the scenario-based urban expansion maps. Simulations with Meso-NH shows that, for the 2006 experience, the center of Toulouse is warmer than the surrounding rural areas by about 6.4°C at 00 LT and at 06 LT. The results highlight an increase of 1 to 2 degrees in the urban air temperature at the beginning of the night and a lost of cool capacity in the scenarios. Furthermore, the results show that big differences in the scenarios are found when exploring the horizontal distribution of the UHI. The increase in the urbanised surface by 2100 leads to a general elevation of temperatures of about 1°C at 00LT and at 06 LT

The efficient generation of 4D BIM construction schedules: A case study of the Nanterre 2 CESI project in France

Building Information Modelling (BIM) can be defined as a set of tools, processes and technologies that are enabled by a digital multi-dimensional representation of the physical and functional characteristics of a built asset. The ‘fourth’ dimension (4D BIM) incorporates time-related project information in the 3D model to simulate and optimise the project construction process. To achieve this, the 3D objects within the aggregated design model must be linked with each activity in the construction schedule. However, the levels of maturity and expertise in using BIM amongst the project participants still varies considerably. This generates collaboration problems within the project and adds further obstacles to the ability to derive full benefits from BIM. Ideally, 4D BIM can be automatically generated, but in reality, because the 3D and 4D models are created separately and at different stages of the project, this is not currently possible, and the process requires considerable manual effort. The research reported in this paper was prompted by the construction of a new training and research building: the Nanterre 2 CESI building in France. It proposes an efficient approach that minimises the effort of creating 4D BIM construction schedules. The CESI four-phase process aims to help project participants to fully exploit the potential of 4D BIM and enables: 1) a clear expression of the 4D BIM objectives; 2) the identification of information requirements and relevant workflows to achieve these objectives; 3) the implementation of a project schedule; and 4) BIM model production to suit the 4D BIM use case. Although the CESI approach was developed in the context of the French contracting system, the observations and conclusions of this study are intended to be generally applicable

Description and validation of a " non path-dependent " model for projecting contrasting urban growth futures

International audienceThis paper presents a model (SLEUTH*) for projecting contrasting urban growth futures.It is derived from the SLEUTH model, which has been modified in order to incorporate an additional spatially explicit factor, and to be used in a fully controlled forecasting mode. Our aim is to spatially allocate urban growth, its amount and pattern, according to predefined prospective scenarios and assuming a non path-dependency approach. This modelling approach aims at being used under a "story and simulation" (SAS) approach, which constrains the model validation. To assess model efficiency, three types of tests have been undertaken: (1) sensitivity tests; (2) reproduction of known changes over a past period; and (3) simulation of changes that break trends. Results show that SLEUTH* conveniently simulates expected urban changes for exploring contrasting scenarios that are the basis for land planning strategies

Automating equipment productivity measurement using deep learning

Measuring the productivity of earth moving equipment help to identify their inefficiencies and improve their performance; however, measurement processes are time and resource intensive. Current literature has foccussed on automating equipment activity capture but still lack adequate approaches for measurement of equipment productivity rates. Our contribution is to present a methodology for automating equipment productivity measurement using kinematic and noise data collected through smartphone sensors from within equipment and deep learning algorithms for recognizing equipment states. The testing of the proposed method in a real world case study demonstrated very high accuracy of 99.78 in measuring productivity of an excavator

Extending the IFC Standard to Enable Road Operation and Maintenance Management through OpenBIM

Open Building Information Modelling (OpenBIM) is a collaborative project management process. Its application to road infrastructures is currently limited. OpenBIM standards for infrastructure are still under development. One of these standards is the Industry Foundation Classes (IFC), which is a data architecture for modelling infrastructure projects. The current and upcoming releases of IFCRoad focus on structuring data for the design and construction phases of an infrastructure’s lifecycle. Semantics of the O&M process phase are not fully integrated within these standards. This paper proposes an extension of the IFC schema to enrich this standard with semantics inherent in the O&M phase of road infrastructures. This extension, based on IFCInfra4OM ontology, allows the OpenBIM process to be fully applied to road infrastructures. Its implementation on a case study relative to the A7 Agadir–Marrakech Highway in Morocco enables, on the one hand, analysis and compliance with O&M management requirements on the basis of a single container: the IFC-BIM-based model. On the other hand, it allows comparison of the OpenBIM process with that of ClosedBIM for the integration of O&M data into BIM for a road infrastructure

Ontology-Based Hazard Knowledge Representation and Identification for Deep Refurbishment Projects

The delivery of construction projects in general can be complex and demanding and presents well-documented challenges to the control of cost, safety, and quality. This situation becomes even more challenging in the case of renovation projects due to the high level of interaction with occupants, especially when they remain in the building over the renovation period. The safety of project participants as well as that of occupants when they are present in the renovation site must be ensured. Although the planning and management of such projects can be greatly enhanced by exploiting some of the advantages of Building Information Modelling (BIM), the process of construction hazard identification and renovation scenarios assessment is still human-based and so requires considerable time and effort. Moreover, there is little research that addresses how hazard identification can best be represented and processed automatically in order to optimise and develop more effective strategies for managing construction projects, particularly those involving the systematic renovation of existing properties for better energy performance. Using BIM along with Artificial Intelligence (AI) tools could help in processing the massive amount of newly-available data and knowledge (e.g., feedback, images captured from smart devices, IoT sensors) that are increasingly obtainable. A prerequisite for doing so is the development of a dedicated ontology that would enable the formalisation of domain knowledge, including associated concepts, relations, and constraints that are specific to renovation project hazard. The authors propose an ontology and demonstrate its application by developing a knowledge-based system for application within the context of deep renovation projects that are part of a large European research project: the RINNO project

Vers une extension du Building Information Modeling aux projets d’infrastructure routière: Cas d’étude d’un échangeur autoroutier au Maroc

Building Information Modeling (BIM) is a technology revolution in the building industry where it has proven itself throughout the life cycle of a building. This reality has led in recent years to an extension of this concept to the Civil Engineering sector for infrastructure projects by deploying scientific research within universities or organized in international groups. The common goal is to facilitate the exchange of data and collaboration around these projects. In this context, our research focuses specifically on road projects and aims to propose a conceptual model for structuring a 3D BIM for this type of infrastructure. This conceptual model is based on the standards applicable in Morocco in addition to recommendations of BuildingSmart in terms of IFC standard. This article provides an exhaustive literature review on the recent advances on integrating BIM in the infrastructure sector. Then, a case study in Morocco is discussed to highlight the requirements and technical constraints that should be taken into consideration for the implementation of 3D BIM in roads infrastructure projects. Key Words: Building Information Modeling, Road projects, InfrastructuresLe Building Information Modeling (BIM) est une révolution de la technologie dans le secteur du bâtiment où il a fait ses preuves tout au long du cycle de vie d’un bâtiment. Cette réalité a mené depuis quelques années, à une extension de ce concept au secteur du Génie Civil pour les projets d’infrastructures en déployant des recherches scientifiques au sein d’universités ou organisées en groupes internationaux. L’objectif commun étant de faciliter l’échange des données et la collaboration autour de ces projets. Dans ce contexte, notre recherche porte spécifiquement sur les projets routiers et vise à proposer un modèle conceptuel de structuration d’un BIM 3D  pour ce type d’infrastructure. Ce modèle conceptuel est basé sur les normes en vigueur au Maroc  d’une part et des recommandations de BuildingSmart en termes de norme IFC d’autre part. Cet article, présente une revue de littérature exhaustive des avancées récentes en termes d’intégration du BIM dans le secteur de l’infrastructure. Ensuite un cas pratique au Maroc est discuté pour mettre en évidence les exigences et les contraintes techniques qui devront être considérées pour l’implémentation du BIM 3D dans les projets d’infrastructure routière. Mots clefs: Building Information Modeling, Projet Routier, Infrastructure

IFCInfra4OM: An Ontology to Integrate Operation and Maintenance Information in Highway Information Modelling

Building information modelling (BIM) is increasingly appropriate for infrastructure projects, and in particular for transport infrastructure. It is a digital solution that integrates the practices of the construction industry in facility management during the whole life cycle. This integration is possible through a single tool, which is the 3D digital model. Nevertheless, BIM standards, such as industry foundation classes, are still in the pipeline for infrastructure management. These standards do not fully meet the requirements of operation and maintenance of transport infrastructure. This paper shows how BIM could be implemented to address issues related to the operation and maintenance phase for transport infrastructure management. For this purpose, a new ontological approach, called Industry Foundation Classes for Operation and Maintenance of Infrastructures (IFCInfra4OM), is detailed. This ontology aims to standardise the use of building information modelling for operation and maintenance in road infrastructures. To highlight the interest of the proposed ontological approach, a building information model of a section on the A7 Agadir–Marrakech Highway in Morocco is produced according to IFCInfra4OM. The methodology is presented. The results obtained, including the IFCInfra4OM data model, are submitted. In the last section, an overview of the IFC extension approach is submitted

Towards an Interoperable Approach for Modelling and Managing Smart Building Data: The Case of the CESI Smart Building Demonstrator

Buildings have a significant impact on energy consumption and carbon emissions. Smart buildings are deemed to play a crucial role in improving the energy performance of buildings and cities. Managing a smart building requires the modelling of data concerning smart systems and components. While there is a significant amount of research on optimising building energy using the smart building concept, there is a dearth of studies investigating the modelling and management of smart systems’ data, which is the starting point for establishing the necessary digital environment for representing a smart building. This study aimed to develop and test a solution for modelling and managing smart building information using an industry foundation classes (IFCs)-based BIM process. A conceptual model expressed in the SysML language was proposed to define a smart building. Five BIM approaches were identified as potential ‘prototypes’ for representing and exchanging smart building information. The fidelity of each approach is checked through a BIM-based validation process using an open-source visualisation platform. The different prototypes were also assessed using a multi-criteria comparison method to identify the preferred approach for modelling and managing smart building information. The preferred approach was prototyped and tested in a use case focused on building energy consumption monitoring to evaluate its ability to manage and visualise the smart building data. The use case was applied in a real case study using a full-scale demonstrator, namely, the ‘Nanterre 3’ (N3) smart building located at the CESI campus in Paris-Nanterre. The findings demonstrated that an open BIM format in the form of IFCs could achieve adequate modelling of smart building data without information loss. Future extensions of the proposed approach were finally outlined