Methodology for 3D Management of University Faculties Using Integrated GIS and BIM Models: A Case Study

Abstract

Three-dimensional virtual modeling is one of the tools being rapidly implemented in the construction industry, leading to the need for strategies based on intelligent 3D models of cities and/or digital twins, which allow simulation by interacting with their real physical counterparts, anticipating the outcomes of decision making. In practice, problems arise when creating and managing these twins, as different data, models, technology, and tools must be used, and they cannot all be combined as desired due to certain incompatibilities. On the other hand, today’s traditional building management demands a more optimized process to prevent errors and enable timely reactions to failures and defects. Managing and using a large amount of complex and disparate data are required, which is why the use of CMMS-type software is common (Computerized Maintenance Management System). However, such software is rarely designed for management in a 3D format, often due to the absence of three-dimensional models of the assets. This research aims to contribute to the technological development of the digitalization of the built environment, providing a simple methodology for generating and managing 3D models of cities. To achieve this, the tools and information useful for generating an integrated GIS 3D and BIM model, and for Computer-Aided Maintenance Management in a three-dimensional format (CMMS-3D), are identified. The final model obtained is used to optimize the three-dimensional management of a classroom building on the “Campus de Las Llamas” at the University of Cantabria in Spain. The results demonstrate that it is possible to integrate digital models with simple linking mechanisms between the existing tools, thus achieving an optimal three-dimensional management model.

1. Introduction

BIM (Building Information Modeling) technology is based on developing a virtual model containing all the information of the physical asset, allowing for various applications and potential uses in both the urban environment and the real building. Three-dimensional GIS (Geographic Information System) modeling, in addition to large-scale virtual navigation, enables the management of quantitative and semantic data for constitutive elements (buildings or urban infrastructures). The use of the various applications offered by these digital models in the public–private management sphere has led to a growing need for learning and implementing the technology, either individually (BIM or GIS) or integrated (GIS and BIM), in the continuous development and improvement of smart cities [1,2,3,4,5,6] and the buildings within them.

Geographic Information Systems (GISs) are effective tools for problem-solving through spatial analysis due to the coexistence of two types of data: spatial and attribute data [2]. They function as a database with geographic information that is related by a code or common identifier to the graphic objects that compose or are added to a digital map, where users can identify problems, monitor changes, and make forecasts with the intention of improving decision making [7,8]. The functioning of this tool is based on storing spatial entities (such as geometry) and referencing them with projections and coordinates on a map. To achieve this, the attributes of the entities are stored in tables and then associated with spatial characteristics to allow the spatial analysis of the data [9]. In order to separate information into different thematic layers and store it independently, a “layer” architecture is employed [10]. The information in each layer contains a subset of features representing the same theme (roads, rivers, buildings, etc.). On the other hand, Building Information Modeling (BIM) is a computer-assisted parametric solution. It optimizes and facilitates the decision-making process throughout the lifecycle of buildings and smart cities [11]. Despite being more than a decade in development, it is considered a relatively recent advancement [9,12]. BIM allows for the three-dimensional modeling of construction projects, facilitating the linkage of all types of information (architectural, structural, facilities, etc.) into a unified parametric model [13,14,15] where efforts are designed, developed, operated, and managed efficiently, allowing for communication in a Common Data Environment (CDE). Therefore, it is a valuable tool for all stakeholders involved in planning, design, construction, operation, and asset management [16,17,18], particularly regarding factors linked to the modern construction industry [19]. The main objective of BIM is to centralize all the information generated by stakeholders in a federated digital model, ensuring work with a single model that serves as a reliable source of information while maintaining project consistency as a whole.

Today’s technicians strive to find ways to create a more controllable, collaborative, fluid, and realistic system between GIS and BIM [20]. Several sources document that both platforms are being explored to attempt to create an ideal graphic database [5,21] with the aim that the resulting integrated model can provide a reliable and functional platform for future urban operation centers, digital twins, and smart cities. This will enable information exchange and interoperability within a single system, facilitating management [15,22]. From a technical perspective, the BIM model is closely related to the “digital twin”. Digital twins are the virtual simulations of cities and/or buildings that allow for feedback by interacting with their physical counterparts and updating constantly [1]. Their generation requires data such as terrain, buildings and their facilities, roads, climate, temperature, humidity, etc. [7]. The accuracy of these digital models depends on the breadth of the data and the level of detail assigned to them [23]. However, in practice, when creating and managing such models, problems arise because multiple software must be used simultaneously in a project, and not all can be combined as desired due to certain incompatibilities in formats [24]. Therefore, although many technical issues related to the integration of GIS and BIM-HBIM have been partially resolved, there is a lack of studies or proposals addressing how to fully integrate or synchronize the respective strengths of these platforms [24,25]. Notable examples of digital twins of cities include the following: Helsinki, Finland [26,27]; Cambridge, USA [28]; Digital Urban European Twin (Pizen, Czech Republic; Flanders, Belgium; and Athens, Greece) [29]; Docklands; Dublin, Ireland [30]; and Singapore [31]. All these twins are GIS digital platforms that lack integration with BIM models. Consequently, although the GIS “entity attributes” can be consulted, there is no access to the “type parameters” of the buildings, and therefore, full availability of the information corresponding to the physical counterpart is not achieved.

Some authors identify the main scope of digital twins in GIS platforms as providing a data storage and analysis tool to deliver semantically rich models [24]. Among other applications of these platforms, urban planning and management, building construction [3], facilities management [32], emergency preparedness [33], and cultural heritage management [10] have been identified.

From the aforementioned, the need for methodologies to integrate 3D GIS models aimed at managing the use and maintenance of buildings through BIM models—not through City-GML, Reality Mesh, or 2D information management systems (CMMS 2D)—is identified. Another emerging need is the lack of integrated GIS 3D and BIM models that function as a virtual library for buildings and their relationship with the environment; particularly, a 3D BIM repository that allows for the preservation of documentation and access to consult, among other things, geometric characteristics, physical condition, defects [34], various construction stages, and the historical circumstances of the building [35]. In other words, there is a need for procedures to create integrated models capable of storing information related to all the processes of the building’s lifecycle management and to facilitate quantitative data processing through the dashboards provided by the 3D GIS platform. Therefore, in this work, we focus on identifying the necessary factors for creating integrated GIS 3D and BIM models and proposing an application of these models aimed at the 3D management of existing buildings (BIM). Thus, during the development of this work, 3D GIS and BIM models were generated and integrated, which helped objectively identify the difficulties encountered during the integration process and also propose a utility (among many others that they could have) and the associated application methodologies with the aim of optimizing the aforementioned three-dimensional management in building construction with CMMS. To achieve this, buildings were modeled in BIM using architectural and MEP (Mechanical, Electrical, and Plumbing) families, with export and integration formats compatible with 3D GIS tools for application in the management of existing buildings (BIM) using some of the available commercial CMMS tools.

2. Methodology for Simulation

Figure 1 illustrates the proposed simulation methodology. It consists of the creation of the GIS-3D and BIM digital models (Phase 1), their integration and enrichment with accurate information (Phase 2), and finally, the development of a potential application of the integrated models (among many other possible applications) aimed at building management (Phase 3).

2.1. Phase 1—Modeling

This phase is organized into two parts: one involving the creation of the GIS-3D environment of the site, and the other involving the creation of the BIM models of the buildings.

2.1.1. Phase 1.1—Creation of the GIS-3D Environment of the Site

This phase involves the 3D modeling of the terrain and the surrounding environment to be integrated with the BIM model (Figure 2). For the generation of the GIS-3D environment, a methodology based on 3 steps is proposed: Step ①—Data management and initial configuration; Step ②—Definition of the terrain and the footprint of the buildings; and Step ③—Generation of the 3D environment of the buildings.

• Step ①—Data management and initial configuration. For “data management,” the first task is to define the semantic level (level of detail and type of terrain) that the GIS-3D model will have, as the management of the initial data and the configuration of the workspace will depend on this requirement. The initial data that must be managed to construct a model are as follows: (a) The cadastral database of the city’s parcels. This database is a 2D GIS layer that contains the municipal and cadastral attribute table, including specifications for the height of each floor of the buildings in the polygons. (b) Data related to the LIDAR (Laser Imaging Detection and Ranging) point cloud of the geographical area. Depending on the country or region, this initial data may or may not be previously available from public administrations; therefore, it is understandable that, in many cases, access to the initial data may require conducting a field campaign for its generation. The initial configuration of the workspace refers to the management and definition of the base map that will contain the GIS platform. This map can be an orthophoto, a street map, or a simple canvas with a solid color.
• Step ②—Definition of the terrain and building footprints. In this step of the methodology, the focus is primarily on the cadastral database of the city’s parcels, from which the “building footprints” necessary to generate the 3D model are extracted. These footprints are 2D polygons that are associated with and integrated into a database or attribute table containing municipal and cadastral data; among these, one of the most important is the specification of the levels of each of the buildings within the polygons. However, it must first be determined whether to include the actual terrain relief. If so, the digital terrain model (DTM) and the Digital Surface Model (DSM) are constructed from the point cloud extracted from LIDAR flights. The DTM is the bare model at ground level, without vegetation, buildings, or other elements on the terrain. In contrast, the DSM stores the highest elevation of the elements on the surface (terrain, vegetation, buildings, etc.) for each cell. The difference between these two models is the Normalized Digital Model or Digital Height Model (DHM), which allows for determining the height of the aforementioned elements above the surface of the terrain.
• Step ③—Generation of the GIS-3D environment for buildings. In this step, the three-dimensional model of the buildings is generated in the GIS platform (not including the BIM models of the buildings). The resulting 3D model will depend on the level of detail (LoD) sought in the project (from LoD1 to LoD4). To generate the buildings in the GIS environment with a level of detail LoD1, the building footprints and their attributes are used. Both are contained in the cadastral database of the city’s parcels, information managed in the previous Step ②. It is common for GIS 3D software to have extrusion tools for building footprints, which are 2D polygons at zero elevation, allowing a uniform total height to be set for the buildings through a user-defined value. Once the height is defined, the building extrusions are automatically generated, resulting in the 3D environment being modeled at a uniform height.

If a more complex model is to be generated, with levels of detail LoD 2 (which already includes the roof slope in the building geometry) to LoD 4, raster tools such as digital aerial photographs, satellite images, digital images, or even scanned maps must be used. These tools should allow the extrusion to be generated, considering the roof slope, from the Normalized Digital Model (NDM) or the LIDAR point cloud. Therefore, the quality of the resulting model will depend on the density of the LIDAR point cloud. Modeling urban environments with a level of detail LoD 3 involves more complex work, as it requires defining multipatches with textures and/or defining exterior elements to the already generated building volumes (such as openings, windows, doors, etc.). The multipatch is a GIS object in which a collection of patches is stored to represent the boundary of a 3D object. These store texture, color, transparency, and geometric information that represent parts of an entity. The patches can be photographs or textures that are stored in the multipatches either automatically or manually. As for models with a level of detail LoD 4, in addition to having the envelope texture (LoD 3), they also define their interior partitions. However, precise definition in GIS is not considered viable. The possible alternative to forming these models is to use commonly employed BIM platforms (e.g., Autodesk Revit) and then import them into the GIS 3D platform. Thus, the building modeled in BIM, composed of parametric construction elements that already have the building’s external and internal parameters defined, does not require the modification of its composition, and upon being integrated into the GIS platform, it is considered to have directly reached a level of detail LoD 4.

2.1.2. Phase 1.2—Creation of the BIM Model of the Building

This phase consists of two steps, as shown in Figure 3.

• Step ①—Preliminary information and data capture. In this step, existing building data are collected to create and populate the BIM model in the next step. The essential information for generating the model includes sketches, plans, measurements, mass position capture (LIDAR point clouds), technical data sheets on the composition of elements, access to family libraries, and more.
• Step ②—Creation of the geometric model. This step involves virtually constructing the building using BIM software. It requires prior knowledge of 3D modeling tools as well as certain technical building concepts. The focus at this stage should not be on achieving highly accurate 3D modeling but on exploring the potential of the BIM model as a tool for building knowledge [36,37].

2.2. Phase 2—GIS and BIM Model Integration Feeding

First, the necessary folders are created on the server to store the files linked to the integrated model (documentary source of the virtual library). Additionally, the access paths or links to all documentation are extracted to be included in the GIS browser, allowing direct access to the information stored on the server, which must be properly specified in both the GIS and BIM models. Next, databases, such as Excel sheets, need to be created, and BIM attribute tables set up to store and link parameters and attribute information. These databases should be linked to the BIM elements and feeding with the information that was not previously integrated into the BIM model (in Phase 1.2). Additionally, pop-up windows that display information about the model elements must be configured in the GIS platform.

2.3. Phase 3—Application to Building Use Management

This application is aimed at managing the use of a building and is developed following a procedure structured into four steps, as shown in Figure 4.

• Step ①—Define spaces, assets, and systems/subsystems, which are the key elements that govern the management of building use.
• Step ②—Set up a 3D CMMS (Computerized Maintenance Management System). This system should allow for the browsing and querying of the information without altering the file and geometric parameters of the original BIM model.
• Step ③—Space management. This step involves ensuring, through the use of the 3D tool, that the different uses and services intended for the spaces are adequately provided.
• Step ④—Request for the resolution of incidents to the corresponding unit. For this purpose, the CMMS will be configured to allow the generation of incidents (failures, alerts, annotations, and queries) in order to identify and notify the stakeholders involved and to propose solutions and/or improvement actions.

3. Case Study

The methodology presented is developed in Santander, Spain, specifically in the urban area of the Las Llamas Campus of the University of Cantabria, Figure 5a. The building developed in BIM is the Civil Engineering School, Figure 5b.

3.1. Phase 1—Modeling

In Phase 1.1, the generation of the GIS-3D environment of the site involved using orthophotos as a base map and a digital terrain model with relief. To represent the latter, we worked with the point clouds from the LIDAR flights conducted for the 2012 National Aerial Orthophotography Plan of Spain (PNOA), which were used to generate the DTM. Both the orthophotos and the aforementioned point clouds were obtained from the “Mapas Cantabria-España” download center [38]. To develop the terrain definition and the footprint of the buildings, the cadastral base of the parcels for each site was utilized. This base, referred to in Spain as “constru”, is obtained directly from the Spanish Cadastre [39]. As shown in Figure 6, the 2D layer “constru” is associated with an attribute table containing information about the parcels, sub-parcels, and the polygonal shapes of the building footprints, which are essential data for developing the subsequent stages.

Since the site is considered to have a terrain with relief, it is necessary to create the DTM and the DSM. To achieve this, the points corresponding to the terrain in the point cloud from the LIDAR flight, shown in Figure 7a, are filtered out. These points are then combined with the orthophoto previously assigned through algorithms implemented in the GIS software (ArcGIS Pro), resulting in a terrain with realistic relief and texture, as shown in Figure 7b.

To generate the GIS-3D environment of the buildings, the “constru” layer is used, which contains a field of the same name in its attribute table. This field describes the heights of each building (Figure 8, Step 1). The height is coded in Roman numerals (e.g., “I” indicates that the building is one story tall, “II” indicates two stories, etc.). However, since the height is not defined by a value in Arabic numerals, a numerical value in Arabic numerals must be assigned to the height variable (in this case, “constru”) in order to generate an extrusion. To achieve this, an algorithm is used (Figure 8, Step 2) that converts the heights defined in Roman numerals to heights represented on a numerical scale in Arabic numerals (Figure 5, Step 3). In this case, an average height of 3 m per floor has been adopted, ultimately generating the environment in LoD 1 (Figure 9).

To obtain a level of detail (LoD) 2, a function is automated to recognize the height of the buildings in the Digital Height Model (DHM) and the height difference between the highest points of the buildings (roofs), thereby defining the slope of the roofs. To achieve a LoD 3 level of detail, a more realistic representation must be assigned to the building envelopes. For this, multipatch features are used, which are GIS objects that store a collection of patches or triangles to represent the boundary of a 3D object. This approach allows texture to be introduced to the buildings through photographs taken of the facades and roofs, or by directly editing the envelope of each building to represent the details of the elements that compose it. Figure 10 shows the models in LoD 2 combined with LoD 3. The LoD 4 level will be achieved with the BIM building to be integrated at a later stage.

In Phase 1.2, the creation of the BIM models of the building involved two models. The first was built from the existing plans and on-site measurements. The second model, focusing on a more specific area of the building, was generated using 3D laser scanning and architectural photogrammetry.

To develop Step ①, Preliminary Information and Data Capture, the process was organized into three parts: (1) positioning work with a topographic station, (2) capture work with laser scans, and (3) capture work through photogrammetry. The positioning work was carried out with a Leica TS13, 5″, robotic total station (Leica Geosystems, St. Gallen, Switzerland), with a total of 10 stations set up around the exterior of the building (facades and intermediate decks). For laser scanning inside the building, a Leica Geosystems BLK360 was used. To georeference the scans, 6″ circular targets were employed, Figure 11a. Considering the specifications of the scanner and the building, 48 scans were deemed adequate. Leica’s Reality Capture software (Register 360 version 2022 and Cyclone 3DR version 2022) was used to process the laser scan data, generating a total of 79 links, Figure 11b. The 48 scans were linked “cloud-to-cloud”, resulting in a combined point cloud. The merged cloud was then registered in the project’s reference system. During the scanning of a building, factors such as cloud cover, fog, smog, birds, etc., can affect the quality of the results. For this reason, the scans were conducted (after consulting weather forecasts) on days when these natural light conditions were not expected to be an issue. In this case, there was no interruption caused by birds; however, there were trees in front of the building’s façade, which were considered during the classification of the point cloud.

Finally, to generate the photogrammetric model of the building, as shown in Figure 12a, a Canon EOS 5DS R digital camera (Canon Inc., Tokyo, Japan) with 40.6 megapixels and lenses of various fixed focal lengths (28 mm, 35 mm, and 50 mm) were used. A total of 948 images were captured (Figure 12b). Before capturing the images, homogeneously distributed targets were positioned. Additionally, natural points that were easily identifiable in the images were observed on the building and used as control or check points. The office work was conducted using the data captured through photographic techniques. The software used for this work was Agisoft Metashape Pro, version 1.8. All the project images were oriented with a ground pixel size (GSD, Ground Sample Distance) of 3.6 mm.

The creation of the geometric model, Step ② (Figure 13), was developed in two ways: using the existing plans as a template, which considerably reduced the need for advanced technological resources (Model 1), and utilizing the point clouds obtained from a 3D laser scanner and/or photogrammetry (Model 2). In the case of Model 1, the creation of the model was more time-consuming due to the unusual shape of the building. It was generated using the Autodesk Revit 2019 software based on on-site measurements and 2D CAD drawings (*.dwg), in PDF format, and printed on paper. As much as possible, the libraries of the existing elements in the software were used for both its architecture and installations, except for the construction of the facades, which had to be modeled with the “mass” tool due to the lack of standard families for this unique enclosure.

In Model 2, with the aim of not modeling all the elements of the building from scratch, the focus was on readjusting the elements of the lower levels of Model 1, which were created previously using Revit 2019, while taking the point clouds as a reference. This approach enhanced Model 1, making Model 2 an accurate geometric representation of the actual building. Since the point cloud was properly referenced, it was necessary to configure certain parameters in Revit 2019, such as the project location, elevation, and the actual north of the project relative to the north of the BIM software’s drawing space. Next, the different levels (heights of the building) were created and positioned; these levels serve as the working planes within the BIM software, allowing the elements of the model created from plans to be adjusted to the dimensions of the point cloud template. Once the process of referencing and locating the levels was completed, the elements of the model were realigned to correspond with the point cloud (Figure 14). The time taken to generate the model turned out to be longer than we expected; therefore, we concluded that the time required to create a model will always depend on the availability of BIM families in the modeling software and the required level of development (LOD). As such, it is not possible to accurately estimate the modeling time for unique existing buildings like the one in this case study.

3.2. Phase 2—GIS and BIM Model Integration and Feeding

In this case, the integration (Phase 2.1) was carried out directly with the Revit file (*.rvt), as ArcGIS Pro v2.7, the GIS software used, is already compatible with *.rvt files. For this reason, the process is quite simplified. Once the file was imported into the ArcGIS Pro “Catalog”, it was linked as a “3D Layer”, georeferenced, and verified to ensure that both the georeferencing and the elevation of the building relative to the terrain were correct, as shown in Figure 15a. Figure 15b shows the integrated GIS-3D and BIM model.

Before loading the integrated GIS and BIM model, it must be ensured that essential elements have been created in the BIM model. To achieve this, families of furniture, sanitary equipment, computers, luminaires, electrical room equipment, and some devices such as fire extinguishers, radiators, and other facilities have been created. This was accomplished by creating families and modifying types (Figure 16).

To feed the integrated model (Phase 2.2), the first step was to configure shared parameters in Autodesk Revit 2019 (Spanish version) that allow us to input the properties of the elements. For example, parameters such as the resistance of a structural element, its creation date, access to the CMMS, the number of available seats in each classroom, and more can be added. The configuration of shared parameters is performed using the Revit Manage tool following a series of defined steps. These parameters were linked via Revit planning tables to Excel sheets, as shown in Figure 16c, enabling automatic updates by external users. This setup allows the Revit model parameters to be populated automatically, creating attribute tables that can then be linked to the GIS platform.

Next, folders were created on the server to contain the files (the documentary source of the virtual library) linked to the model. Additionally, paths or access links to all the documentation were extracted to be included in the GIS browser, enabling direct access to the information stored on the server. To accomplish this, we utilized the websites of the University of Cantabria [41] and the Building Technology Group [42]. We copied the links where information related to the Civil Engineering School can be found, along with other useful navigation information, such as PDF plans, department information, and courses offered.

Excel sheets were also created to link Revit planning tables and ArcGIS Pro attribute tables. Furthermore, the information feeding the Excel sheet was synchronized using the Revit plugin “Export–Import Excel”. In some cases, information was entered manually. Finally, pop-up windows were configured to display the information consulted in the integrated model. These pop-up windows appear when the cursor is clicked on a specific element for consultation.

3.3. Phase 3—Application Oriented to Building Use Management

Step ① defined the spaces, assets, and systems/subsystems used in this simulation. Specifically, the teaching classrooms, computer equipment, study areas located in corridors, departmental areas, and the exhibition area were identified. In Step ②, the CMMS Revizto (Spanish version) was configured, which allows for 3D navigation with the capability of generating three-dimensional annotations in the model, as well as the interaction and scheduling of these annotations with the various stakeholders involved. To do this, the Revit model (*.rvt) was first linked to Revizto (Figure 17). Next, a link was established in the GIS-3D and BIM model within ArcGIS Pro through the attributes of the elements; thus, clicking on one of these elements displays a pop-up within the GIS-3D environment, allowing for instant access to the Revizto CMMS (Figure 18).

In Step ③, the implementation of space management for some of the most important services provided by the Civil Engineering School was simulated, specifically concerning the management of teaching classrooms. For this purpose, these spaces were configured to access information related to the academic activities conducted within them. Thus, through the shared BIM parameters of the developed virtual 3D model, a wide variety of information can be accessed, such as the calendar hosted on the server (Figure 19a) or links to attend video conferences/online classes (Figure 19b), as shown in steps 3–5. To monitor classroom occupancy capacity, a GIS control panel was configured, as shown in Figure 19c. An Excel spreadsheet was created and linked to the BIM model, which was then integrated into the 3D GIS model along with the BIM model. The Excel spreadsheet is populated with data (parameters) regarding the classrooms, specifically the number of available seats in each classroom. Next, an analysis chart is constructed by selecting one of the options available in ArcGIS Pro, ensuring that it represents the desired attributes of the family and/or space to be monitored (in this case, classrooms). A bar chart was chosen because it allows for a parallel comparison of the occupancy capacity of the classrooms.

For the management of computer equipment, access to the computer terminals in the computer rooms was configured (Figure 20). To access the terminals, simply select the classroom in question in the 3D model (1) and click on the “Remote Access” parameter (2), which is linked to the UC “unicanLab” portal. Once access is granted, the portal will select a computer in the designated room where the user must identify themselves with their UC username and password (3).

It is also possible to consult the technical data sheet for the computer equipment and teaching aids in a specific classroom (Figure 21). To do this, select the desired classroom from the “Rooms” tab (1) and click directly on the computer in the room (2). Then, access the properties window and click on the “Technical Sheet” parameter (3), which will open the link to the file containing the sheet (4).

Another important utility is the consultation of relevant information for course coordination, which can include, among other things, the courses/subjects taught in the classroom, the number of available places, whether there is an electrical connection for laptops at the desks, and the ability to report detected breakdowns and/or warnings.

For the management of study areas located in corridors (Figure 22), since these are spaces in free circulation areas, their management within the Revizto model consisted of the 3D visualization of the corresponding furniture, the location of WiFi terminals, and the recording of incidents (such as a lack of WiFi connection, damage to furniture, etc.).

In the case of managing department areas, it involved configuring direct access to the web page of these functional units, allowing for the direct consultation of their information (Figure 23). To do this, access the “Rooms” window and click on “ETSICCP SCHOOL” (1). Then, consult the “Properties” window and click on the “Departments” parameter (2), which leads to the Web-UC section of the Civil Engineering School, where the various departments are listed (3).

Finally, the management of the exhibition areas (Figure 24) serves two important roles: the first is the possibility of including virtual reality visualization, which is useful for 3D navigation, and the second is the coordination of the available spaces. Since these areas change depending on the timing of events, their status must be constantly updated in the virtual model. For this reason, a point cloud was integrated to represent the current information of one of the exhibition areas in the model, as this was considered easier than creating a family or element in the BIM model.

In Step ④, which involves requesting the resolution of incidents and faults from the corresponding unit, the model is ideal for traceability tasks because it allows for the locating of maintenance or work requests as annotations in the 3D model. For example, a correction request was simulated regarding the installation of the “50th Anniversary” sign for the Civil Engineering School of Santander. Thus, the person in charge interacted with the correction regarding the placement of the sign, sharing documentation throughout the process, both on-site (using a mobile device) and in the office (through the desktop application), with all the management actions being recorded and stored in real time (Figure 25).

In order to compare the main results obtained, in relation to the existing challenges in digital building management, a SWOT analysis is presented in

Table 1. SWOT analysis of the simulation results.

Strengths	Weaknesses	Opportunities	Threats
Predicting maintenance through simulation	The requirement to manage and use complex and disparate data	The need to optimize digital asset management	The lack of resources for the 3D modeling of installations
Optimize, through BIM, the management and maintenance of historic buildings	The lack or insufficiency of information for Facility Management	The need to optimize the Computerized Maintenance Management Systems/Software (CMMS)	Three-dimensional models are usually architectural
Organize in a 3D environment the information generated throughout the design and construction process	Losing information between the construction and operation phases	Improved accessibility of high-capacity Internet services	The high cost of software licenses CMMS
Managing public spaces and Infrastructure	BIM software is not designed to perform Facility Management	The potential development of applicable sensors	Incompatibility of 2D and 3D model connection formats
Access to all the parametric information of the model	The shortage of resources for the digitalization of public assets and spaces	Excellent source of the statistical management of BIM parameters and GIS attributes	Digitalization technology is still in its infancy

.

4. Conclusions

With the aim of contributing to the technological development of digitalization in cities and improving building management processes through the navigation of the built environment that supports it, the research presented here proposes a methodological process to integrate digital GIS-3D and BIM models, linked to other transversal technological resources such as tools applicable to Computerized Maintenance Management Systems (CMMS), which allows for the synchronization and management of information contained in both models.

In the case of the GIS-3D model, modeling presented a challenge in achieving the optimal volumetry of the city in 3D since the volumes are extruded from algorithms that use the footprint of the buildings and the point cloud from LiDAR flights as starting data. This process often results in graphic errors, largely due to the insufficient quality of the latter. Depending on the project’s requirements, the laser scanner data acquisition service can be resource-intensive, which may occasionally hinder the realization of a project. Although the results of laser scanning are more accurate than those of photogrammetry, many technicians continue to use the latter because it is a tool that can provide good and sufficient results for BIM (and other possible uses) depending on the case. Moreover, it is a more economical method than laser scanning. The BIM model generated from 3D laser scanning is more accurate, matching the actual dimensions of the existing building (as-built, geometrically speaking).

On the other hand, when plans of the building are available, generating BIM models from them is a more practical and faster option, as not having to carry out fieldwork to extract measurements using laser scanners, along with the subsequent office work associated with processing this information, allows for additional time to be optimized for the development of the BIM model. The ability to create shared parameters, where information available on paper can be stored after digitization, combined with the capacity to link the model with Excel—enabling individuals without advanced knowledge of computer-based architectural design to update the model information—represents a significant achievement in the digitization process of BIM models.

The greatest advantage identified in integrated GIS and BIM models is the ability to contain geometric or semantic information in 3D format as a virtual library, which can be accessed by stakeholders. This accessibility helps evaluate and make decisions regarding process development, consequently reducing resource consumption (time, money, etc.). Regarding conclusions about the simulation of building management, it is worth mentioning that the system was well received by the stakeholders, as it demonstrated that they could simulate or, rather, develop the tasks assigned to them in the management of the service in the case study using the software. The results of the simulation are positive, as the model showed that all the activities related to the building service could be organized and that it allowed for efficient and direct communication between different stakeholders, keeping the information updated and shared in real time from any location, resulting in a fully optimized and efficient process.