Visualization of CCTV coverage in public building space using BIM technology
© Chen et al.; licensee Springer. 2013
Received: 15 February 2013
Accepted: 1 May 2013
Published: 12 June 2013
Nowadays, the use of Closed Circuit Television (CCTV) systems is effective for monitoring traffic, preventing crime, and ensuring safety in many public spaces. However, the effectiveness of CCTV coverage is often achieved through design experience and trial-and-error, instead of being evaluated and visualized using a robust approach.
Firstly, a method for simulating varifocal CCTV lenses in order to attain different fields of view was developed, allowing real CCTV views to be approximated by adjusting the parametric properties of simulated CCTV cameras in the 3D BIM model. Secondly, an API (Application Programming Interface) plug-in program for a commercially available BIM tool was developed to facilitate the parametric modeling of CCTV systems and the evaluation of the CCTV coverage.
A complete BIM model of an MRT (Mass Rapid Transit) station was chosen as a case study to apply the developed approach to the examination of CCTV coverage. Finally, the overall coverage of the CCTV systems for the MRT station were demonstrated visually and studied in the station's BIM model.
This research has developed a robust visualization approach for evaluating the coverage of CCTV systems in public building spaces. The developed approach is based on Building Information Modeling (BIM) technology and is capable of simulating CCTV systems in a 3D virtual environment in order to evaluate the CCTV coverage.
KeywordsBuilding Information Modeling (BIM) Closed Circuit Television (CCTV) coverage Visualization approach Parametric modeling
In the 1990s, Closed Circuit Television (CCTV) systems were used for public security and crime prevention in urban cities in England. The British government and the police were both in favor of the use of CCTV systems. On the other hand, there was a huge controversy in relation to its cost, benefits, legitimacy, and privacy issues despite its effectiveness in crime prevention (Harris et al., 1998). Nowadays, CCTV is widely used in many public spaces in order to prevent crime, monitor traffic events, and ensure public safety (e.g. Aguado et al., 2009; Teague et al., 2010).
Once a CCTV camera is installed in the field, its relocation is expensive. Therefore, a thorough design of CCTV layouts should be conducted in advance of positioning in order to ensure proper siting and mounting (Lee et al., 1995). Currently, the positions and orientations of most CCTV systems are designed based on 2D diagrams such as floor plans. This may cause many spatial design conflicts with other systems due to a lack of the third dimension in the design space, and lead to unnecessary overlapping of CCTV coverage. Additionally, both CCTV screen views and CCTV coverage are usually unknown before construction is completely finished.
Building Information Modeling (BIM) has been a rapidly-developing technology in the Architecture, Engineering and Construction (AEC) industry in recent years. Using BIM technology, an accurate building model with precise geometry and other AEC-relevant data can be constructed in a virtual environment throughout the lifecycle of the building. BIM models are thus referred to as computer-generated models that utilize parameters of model elements to support the construction, fabrication and procurement activities required to realize the building (Eastman et al., 2011: 1–2). The 3D modeling and visualization provided by the BIM software can effectively discover and solve hidden problems that previously could not be detected until construction was completed. By using different viewpoints, reviewers are able to conduct interference checking between systems and thus reduce unnecessary design conflicts. Also, the computational representation of a BIM model can offer a simultaneous visual representation, which allows discussion of design ideas and analytical tests during the BIM-based design process (Wang et al., 2010).
One of the major differences between BIM and conventional 3D CAD models is the linkages among model views. A conventional 3D CAD model describes a building by independent projected views such as plans, sections and elevations. If one of these views is modified, all other related views must be revised and updated manually; such a process is prone to human error. In addition, these 3D drawings contain only graphical entities, such as lines, arcs and circles. In contrast a BIM model consists of parametric objects that are defined in terms of building model elements and systems, like spaces, walls, beams and columns. BIM software is able to automatically generate conventional building plans, sections, and elevations directly from a 3D BIM model as well as photo-realistic 3D renderings, which up to a few years ago could only be produced by special visualization packages but can now be produced with little additional effort (Sah and Cory, 2008; Azhar, Hein and Sketo Hein and Sketo 2008). Furthermore, a BIM model is equipped with other non-geometric information needed for tasks in the lifecycle of the corresponding building or facility, including physical properties, functional characteristics, spatial relationships, etc. Therefore, it allows designers, engineers, and other project participants to visually examine the planning and design outcomes in a more intuitive way with richer information support. By the same token, the use of an existing BIM model to examine the coverage of CCTV systems can be a highly efficient and low cost auxiliary approach to aid CCTV layout design.
The objective of this research is to develop a robust visualization approach for evaluating the coverage of CCTV systems in public building space. The expected benefits can be summarized as follows: (1) to ensure intended CCTV coverage and reduce design conflicts with other systems; (2) to shorten the time required to setup CCTV cameras during construction; (3) to provide a better communication medium among CCTV system designers, project owners and facility operators.
In the following sections, the methods and process of modeling a CCTV system in a BIM environment are presented first. Then, an MRT (Mass Rapid Transit) station was chosen as a case study for demonstrating the results of this research. Using the Autodesk Revit Architecture (Autodesk, Inc 2010a) (hereafter shortened to Revit) along with the BIM model of an MRT station, this research employs BIM technology to integrate CCTV systems into the virtual building space of an MRT station. Finally, virtual CCTV screen views were simulated so that the CCTV coverage could be clearly visualized and studied in the virtual environment.
This section explains the process of modeling a CCTV system in a BIM model. This research uses Autodesk Revit as the development platform because the BIM model of the MRT station used in the case study was originally modeled by Revit. Revit provides a user-friendly and powerful 3D modeling design environment and can import 2D AutoCAD files for assisting with the model construction. It also provides a collaboration platform with a centralized database so that all changes can be synchronized to the cloud server (Azhar, Nadeem et al., 2008). Moreover, Autodesk supports an Application Programming Interface (API) for users to extend the core functionality of Revit through plug-in programs. In this research, a complete solution in Revit for simulating CCTV systems in BIM models is developed.
Using Revit cameras as CCTV cameras
Simulating the varifocal lenses of CCTV cameras
Different CCTV cameras in a building have different fields of view (FOV). Based on the optical properties of camera lenses, different FOVs can be achieved by changing the focal lengths of the lenses. Thus, the first step in the simulation of CCTV systems in BIM models is to come up with an approach to simulate the varifocal lenses of CCTV cameras.
According to Eq. (1) and the default film dimension, 36 mm, the focal length of 60 degrees FOV is calculated to be 31.2 mm.
According to the principle of similar figures, the width of the crop region size corresponding to 60 degrees FOV can be calculated by multiplying 150 mm (i.e., the width of the default crop region size) by a ratio of (38.6 mm/31.2 mm), in which 38.6 mm is the default focal length, and the result is 185.6 mm.
According to the screen aspect ratio, the height of the crop region size can be calculated by multiplying 185.6 mm by 3/4 and the result is 139.2 mm.
Configuring revit cameras with parameter analysis
Field of view (FOV):
As mentioned in the previous section, a CCTV camera uses a varifocal lens to attain different FOVs, which are determined according to its requirements, location, etc. Since this research aims to examine the existing design of CCTV systems, all the FOVs of the CCTV cameras should be predefined by CCTV designers.
Camera height (H):
The camera height relates to the ceiling height. This dimension is measured from the floor elevation to the ceiling elevation. The corresponding parameter of the Revit camera is “eye elevation”.
Target height (h):
Normally, the target of CCTV cameras are people, therefore, the average height of humans is adopted as the target height. The corresponding parameter of the Revit camera is “target elevation”.
Subject height (%) and Subject distance (D):
Rotakin, developed by the Home Office in the UK, is the only device specified in BSI EN 50132–7:1996 for testing CCTV camera performance. The Home Office also offers an operation manual (Cohen et al., 2009: 8–9) that defines the concepts of subject height and subject distance. Depending on the nature of the human activity to be observed, five general observation categories have been defined for different purposes, including monitoring and control, detection, observation, recognition, and identification. These five categories are based on the relative size of a person that appears on a screen (see Figure 6). This is defined as the subject height, a percentage of the height of a person divided by the height of the screen. For a specified subject height, the maximum distance from which a person can be seen on the screen is defined as the subject distance (i.e. a person would be too small to be seen on the screen beyond the subject distance for the specified subject height). An independent consultancy company provides an online lens calculator based on the standards of the Home Office, LensCalc (CCTV Advisory Service, 2008), to help determine the subject distance required to achieve specified subject heights for different combinations of sensor size, subject height, and lens focal length (see Table 1). Please note that the subject height is used to specify a particular system requirement rather than to define a general standard. Additionally, the related guidelines were first developed in the PAL (Phase Alternating Line) standard, which is a color encoding standard for analogue television and has been commonly used in the design of CCTV systems in public areas. Nowadays, a smaller subject height may be accepted through the use of new cameras with higher resolutions. Please refer to the CCTV Operational requirements manual 2009 (Cohen et al., 2009: 9–10) for more information.
Real angle of depression (θ):
Subject distances for different combinations of the subject height and the FOV
In addition to the parameters above, the CCTV coverage is also shown in Figure 5. The red trapezoidal area reveals the coverage area of a certain CCTV camera that covers the area where persons standing can be seen by the CCTV for a specified subject height. The measure of that red trapezoidal area can also be calculated and displayed in BIM models using Revit as discussed later in the Evaluation and visual representation of CCTV coverage section.
Simulating virtual CCTV screen views
As previously mentioned in the Using Revit cameras as CCTV cameras section, a Revit camera object that provides a 3D perspective view can serve as the CCTV camera in the Revit BIM environment. That is, virtual CCTV screen views can be simulated by using Revit camera views if appropriate parameters are applied.
Plug-in development with revit API
Autodesk has released the Revit API (Autodesk, Inc 2010b) to allow users to develop plug-in programs in order to automate repetitive tasks, thus extending the core functionality of Revit. With Revit API, it is also possible to perform customizations based on the requirements of users. The program developed with Revit API is called Revit add-in that supports all .NET compliant languages for programming.
This research uses Autodesk Revit Architecture 2010 as the BIM software. It also provides an API to enable advanced users to develop external applications in order to incorporate BIM-based parametric design methods (Wang et al., 2010). The API offers access to the active Revit document and its corresponding BIM database. Information can be retrieved from the database, and any External Commands available in the Revit API can perform basic database operations (Yan et al., 2011).
To enhance the performance of Revit in the evaluation of CCTV coverage, a plug-in API program, called CCTV setup advisor for Revit cameras (hereafter shortened to CCTV setup advisor) is developed in this research with the following two considerations. Firstly, it is more succinct to integrate all related functions and steps in Revit to a single interface because modeling CCTV systems in BIM models requires a sequence of procedures. Secondly, it is more time efficient for users to configure many parameters in a single interface due to the fact that there may be many CCTV cameras required even in a single building space.
CCTV setup advisor, therefore, has two main functions developed with BIM technology: (1) simulating varifocal CCTV camera lenses by Revit cameras and (2) configuring the parameters of Revit cameras to obtain virtual CCTV screen views and optimized real angles of depression. Revit cameras in the Revit API are read-only; therefore, no parameter of Revit cameras can be modified through external API commands. Thus, it is advisable for users to manually input the values of the parameters suggested by the plug-in program.
Additional file 1: The CCTV setup advisor. (MP4 6 MB)
Results and discussion
After successfully modeling a CCTV system in a BIM-based virtual building space, this research conducted a case study to examine CCTV coverage. To make the BIM-based virtual environment correspond better to a real situation, a BIM design model of an MRT station under construction in Taipei city was adopted for the case study.
When the MRT train stops at a station, the train driver can monitor the movement of passengers getting on and off the train via CCTV systems. This helps to ensure the safety of passengers.
Station staff can monitor the activities in the station through the CCTV systems so that proper reactions can be made promptly in the case of an emergency.
The traffic control center manages the operations of the entire MRT system with the help of the CCTV systems in MRT stations. The operators can visualize all situations in MRT stations and respond correctly to ensure the safety of the trains in service.
Station staff can monitor, through CCTV systems, the traffic flows of passengers at all entrances and exits of the station and ensure that entry/egress is smooth.
The purposes of application discussed above also define the design requirements of the CCTV systems in the MRT system. For example, CCTV cameras are needed in certain locations on the platform to ensure full coverage of the movement of passengers getting on and off the trains. They are also needed at all entrances and exits of stations for good coverage of passenger traffic flows.
Modeling of smoke curtains and ceiling signboards
In order to examine any design conflicts between CCTV systems and other systems, several architectural components in an MRT station that may block the views of the CCTV cameras need to be modeled as parametric elements in the BIM model. These include smoke curtains and ceiling signboards.
Thus, this research models the smoke curtains and ceiling signboards as parametric elements in the Revit model. Among predefined system family types in Revit, the Wall element is most appropriate for modeling parametric smoke curtains and ceiling signboards. By means of modifying several Wall properties, such as base constraint, base offset, top constraint, top offset, and thickness, the appearance of Wall elements can resemble smoke curtains and ceiling signboards. The elements with different locations, heights and sizes can be easily and parametrically modeled in the BIM model.
Process of modeling CCTV systems with CCTV parameter advisor
The second step is to determine the other two necessary parameters for the Revit cameras within reasonable ranges: the eye elevation and the target elevation. As previously mentioned in the Configuring Revit cameras with parameter analysis section, the eye elevation depends on the camera height, while the target elevation depends on the target height. Normally, the reasonable range of the camera height may be between 2.3 and 2.5 meters in the environment of an MRT station. Also, it is appropriate to apply the average height of the Taiwanese people to the target elevation, that is, approximately 1.7 meters.
More importantly, the CCTV setup advisor can suggest an optimized real angle of depression for the specified CCTV camera (see Figure 19). This may help to reduce the time for installation and adjustment of CCTVs because the best angle of depression for a CCTV camera has been determined in advance under user-desired conditions (i.e. an optimized real angle of depression exactly corresponds to a virtual CCTV screen view simulated by the Revit camera).
Checking for design conflicts
Prior to the use of 3D technology, detecting interferences between systems was both difficult and time-consuming. Nowadays, 3D BIM technology helps detect clashes in advance through more sensible visual presentations and more seamless collaboration platforms (Eastman et al., 2011: 272–273).
One of the aims of this research is to take advantage of BIM technology for inspecting in the design phase whether a desired location for CCTV camera installation is suitable in the future construction phase. Once CCTV screen views can be simulated via Revit cameras, it is simple to check if anything blocks the view of the CCTV camera in the BIM model. Examples of these are smoke curtains and ceiling signboards, which can be modeled as parametric elements in the BIM model of the MRT station. Such design conflicts must be discovered in advance and eliminated to reduce the installation and adjustment time required for the setup of CCTV cameras.
However, it is difficult to give a precise definition of design conflicts due to the fact that how seriously something blocks the CCTV camera’s view may depend on subjective assessment by the operators. A more objective way to evaluate whether there is a clash is to use the optimized real angle of depression suggested by the CCTV setup advisor. Once an optimized real angle of depression is applied, most interference is supposed to be avoided. If there is still an obstacle blocking the CCTV camera’s view, this implies that the parameters of the CCTV camera should be reset, including the camera height, target height, FOV, or even its original location.
Evaluation and visual representation of CCTV coverage
Even with the highly developed VR technology used today in the construction industry, CCTV systems are more often designed in a 2D environment. As CCTV systems have been introduced in 3D BIM models in this research, it is convenient to display the overall 3D environment and the CCTV coverage area through both 2D and 3D VR approaches.
Assuming that the coordinates of the point O and the point Q are (0, 0, H) and (D, 0, h), respectively.
The length of .
The length of , where the point Q is the midpoint of the line segment, .
Based on the screen aspect ratio (i.e. 3/4) as mentioned in Simulating varifocal lenses of CCTV cameras section, the coordinate of the point R is .
The coordinate of the point P is and the points of O, P and R are in the same straight line. Therefore, the length .
Although the red trapezoidal area can be calculated through the mathematical approach, it is more convenient and efficient to use the “Filled region” function in Revit. Once an area formed by a closed loop of lines is specified, the corresponding filled region can be shown on the floor plan view, and the measure of that area can be calculated automatically.
After all “filled regions” are created for all CCTV cameras in the MRT station, it is crucial to check if there are any overlapping areas among those filled regions. If so, the filled regions with overlapping areas must be redrawn as a single closed loop area to obtain accurate calculations of the areas. Although this may take a lot of time to do, especially when there are many CCTV cameras in an MRT station, it is a necessary step.
Additional file 2: The CCTV coverage in the MRT station. (MP4 10 MB)
This research has developed a robust visualization approach for evaluating the coverage of CCTV systems in public building spaces. Firstly, a method for modeling CCTV systems in virtual building spaces is presented. The emphasis is placed on offering a visual representation of the CCTV coverage in a BIM-based virtual environment. By simulating varifocal lenses and configuring the parameters of Revit cameras, the developed approach simulates the CCTV screen views to provide a better visual demonstration of the working of the CCTV systems. This is advantageous in the checking of design conflicts and effective communication between owners and contractors. The filled regions displayed in the 3D environment are also apparent, allowing accurate visual evaluation of CCTV coverage. Additionally, the plug-in program developed using Revit API, (i.e. CCTV setup advisor) is very helpful for processing the repetitive task of setting up the values of Revit camera parameters. Finally, in the case study of an MRT station, the developed approach is shown to be effective and can be widely applied to other building spaces under similar conditions.
The authors would like to thank National Science Council, Taiwan for sponsoring the College Student Research Training Fellowship on this research, Department of Rapid Transit Systems, Taipei City Government for supporting all related data, drawings, and materials needed by the research, Sinotech Engineering Consultants, Ltd. for sharing a complete BIM model of an MRT station, and ST Electronics (Taiwan) Ltd. for supporting technical assistance of CCTV systems and its practical experiences. Also, the authors appreciate all the comments and suggestions received when an earlier version of this paper was first presented in the 12th International Conference on Construction Applications of Virtual Reality (CONVR 2012), Taipei, Taiwan (Chen et. al, 2012).
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