Automated Code Compliance UpdatesAECbytes Feature (May 25, 2017)

In October 2015, I published an article on the state of the art of automated code checking in AEC (“Automating Code Compliance in AEC”), in which I found that it had not made as much progress as one might expect, given the early attempts to automate code checking, even prior to BIM. It is indeed mystifying as to why—now that intelligent model-based building design (i.e., BIM) has been established as the go-to technology in the AEC industry, enabling a building model to be computationally analyzed—we are still dumbing down these intelligent 3D models into 2D drawings and checking them manually for code compliance as we were doing in the drawing/CAD era. It is obvious that we have not yet been able to “harvest” the intelligence in a BIM model to make the code-checking process easier, compared to how we have been able to utilize BIM to improve pretty much every other aspect of building design, analysis, construction, and slowly but surely, even operation and maintenance.

Following the publication of my 2015 article, I received several comments, some of which were pointers to additional work being done in the area of automated code checking that I was not aware of. This follow-up article explores these and some additional efforts I came across in the course of my research on automating code compliance, both on the commercial front as well as in academia, where this is still very much an open topic for investigation.

Commercial Solutions

Given that code-checking for compliance by regulatory agencies is still currently being done on the basis of 2D drawings, some solutions for compliance review are focused simply on digitizing that process, eliminating the need to print and submit paper copies of drawings to obtain approvals. One example of such a solution is e-PlanSoft, which is actually a suite of three products targeting AEC firms as well the state, county, and municipal agencies responsible for code creation and enforcement: e-PlanCheck, which enables agencies with code enforcement duties to review applicant submitted building plans, architectural drawings, and supporting materials via a Web browser, and allows multiple users within the agency to perform the review concurrently; e-PlanReview, which is essentially an online electronic document review application that allows AEC firms to upload and review drawings and documents collaboratively, with the ability to add mark-ups and comments as well compare drawings through overlays or side-by-side placement; and e-PlanAssessment, which is similar to e-PlanReview except that it is focused on site and facility inspections.

Essentially, the suite of e-PlanSoft products is similar to electronic publishing and review, a technology that is already used by most AEC firms on their projects to collect the project information in digital format in one location where it is accessible to all team members to collaborate on. However what still makes e-PlanSoft a useful first step in the digitization of the code-checking process is that it is bringing regulatory agencies into the digital umbrella as well, with its e-PlanCheck product developed specifically for them to review projects for compliance electronically and collaboratively, without resorting to pen and paper. Obviously, we should not be printing and shipping hard copies of documents in this day and age. Thus, while e-PlanSoft is hardly revolutionary—it is not attempting to do any kind of automation—it is definitely useful, and has been incorporated into several portals that offer building permit regulatory services such as SmartGov, Accela, FastTrackGov, and  PermitTrax (Figure 1).

Figure 1. e-PlanSoft’s e-PlanCheck product integrated with Accela’s permitting system, Citizen Access.

Another code-review solution that I learnt about is also 2D-based, but it applies some inferencing smarts to the drawing to extract meaningful building-related data from it and then does some amount of automated code-checking on the basis of this data. This is the Smart DCR application developed by a company in India, Vinzas Solutions, to help speed up the process of building plan compliance check in accordance with local building codes (called “bye-laws” in India). The product was developed and was being used prior to the BIM era when 2D was the norm, and even now, the rationale for not using BIM is that the generation of BIM models is cumbersome and expensive. Also, most of India’s AEC industry is still using 2D, so the strategy behind Smart DCR to infer intelligence from a 2D drawing for compliance checking makes a lot of sense.

Smart DCR is targeted towards regulatory agencies rather than AEC firms, extracting the relevant data from the submitted drawings, comparing them with the respective authority's building bye-laws, and generating a report detailing compliance of each parameter with the bye-laws. It allows scrutiny officers to complete the approval process in few hours rather than days, weeks, or even months that the typical manual scrutiny process takes. Similar to e-PlanSoft’s solutions, Smart DCR can also be integrated into an e-Governance solution where the e-submission and other processes are already automated and the plan scrutiny is still a manual process. It should be noted that for the data extraction to work, the drawings have to be created following certain specifications (Figure 2 shows some examples), so Smart DCR is not magically extracting intelligence from any kind of building drawing!

Figure 2. A couple of examples of specific instructions about how the drawing has to be created for Smart DCR to be able to analyze it. There are over 50 such instructions.

The third solution that was brought to my attention for code-checking actually uses BIM. It is called SMARTreview APR, and it automatically checks a BIM model for compliance with the International Building Code (IBC). It is available as an add-in to Autodesk Revit and works—like most applications these days—as a cloud service that analyzes the Revit model and provides a comprehensive report of which aspects of the design failed and which passed, as well as which provisions of the IBC apply to the design in the first place (Figure 3). It is targeted towards designers, allowing them to check their designs for code compliance before submitting them for approval.

Figure 3. Graphical display of the results of a SMARTreview APR check of a Revit model, as well as a detailed report. .

SMARTreview comes closest to the vision of truly automated code checking, although what is also needed is similar software at the regulatory end, allowing code-checkers to also automatically check a building model for compliance. There doesn’t seem to be any technological reason why an application like SMARTreview APR cannot be used at the design end (to ensure a building is code-compliant) as well as the regulatory end (to check a submitted building for code-compliance). It would, however, need to be integrated with larger building permit regulatory services similar to how e-PlanSoft’s products have been integrated.

SMARTreview has its roots in academia and comes from the work of Mark Clayton in the Department of Architecture at Texas A&M University. It was brought to my attention by Paul Teicholz, who will be discussing it in more detail in the next edition of “The BIM Handbook.”

Academic Research

While SMARTreview is an example of a commercial solution that originated as academic research, code-checking is still very much an active area of research, as evidenced by a simple Internet search on “research in code checking for buildings.” It shows work that is being in automated code-checking at universities across the globe, including the US, UK, Canada, New Zealand, Portugal, Germany, China, and many more.

One research initiative I am aware of that seems particularly promising in its ability to be developed into a real-world tool is the SEEBIM (Semantic Enrichment Engine for BIM models) project at the Technion – Israel Institute of Technology. It has a somewhat different approach that is very well articulated by Rafael Sacks who is supervising this research and who wrote in to tell me about it in response to my 2015 article. His description of SEEBIM and the rationale behind it is copied here verbatim:

“The major barrier to automating code compliance was and remains the content of the models. In order to check whether a corridor meets some minimum width requirement, for example, the space itself must be defined, the space function must be identified as a corridor, and the check needs to be performed along the full length of the corridor, through turns and doors. The geometry is not enough – if the semantic information of the design subject and intent is not explicitly made available, the code check cannot be performed.

While BIM is of course a major improvement over any kind of 2D representation, the concepts required for most code checking are still absent from most models. There are two reasons for this:

  1. BIM modelers are not concerned with making their models explicit in every way. Why make the extra effort to explicitly model a ‘space’ object when modeling four walls is sufficient for all of your immediate needs?

  2. Different design codes and building codes in different jurisdictions define their rules with different concepts and enumerated values, so that even if one could persuade modelers to model in a particular way, they would need to tailor their work carefully for every different check.

People can quite easily infer the meaning and design intent of a building from 2D drawings if they have the appropriate professional background and training, and thus the task of code checking is still in the hands of people. Despite the resources devoted to the problem described in your article, code-checking has not yet been successfully automated.

If one could shift the onus of generating explicit information from the BIM modelers to the receiving applications, in this case the code-checking applications, then it becomes possible to envisage code-checking systems that can receive generic BIM models and ‘semantically enrich’ them as a pre-processing stage before checking them. This is the approach we have adopted in the SEEBIM research (Semantic Enrichment Engine for BIM models) – see:
http://onlinelibrary.wiley.com/doi/10.1111/mice.12128/abstract
http://www.graduate.technion.ac.il/Theses/Abstracts.asp?Id=28181

The idea is to embed the domain knowledge of a person in an expert system for pre-processing. A trained code-checker, for example, can look at a BIM model and see the corridors or any other semantic constructs by virtue of their understanding of the spatial topology, materials, object types, and any other cues that are present, and add the ‘corridor’ space object with its function as a preparation for code-checking. In general, their process of inference can be expressed as a set of ‘if-then’ rules that can be evaluated against a model in order to add new facts. This has been shown to work in the domains of precast concrete modeling, quantity take-off and cost estimation for precast concrete, and a new project has just begun to apply the approach to the compilation of highway bridge models (see http://www.infravation.net/projects/SEEBRIDGE)

While the SEEBIM approach is still in the research stage, it may offer an alternative to the current need for rigorous preparation of BIM models that is currently necessary for any kind of code-checking, and make automated code-checking possible in the future. A major advantage is that it may be better aligned with the business interests of the BIM software vendors, in that the cost of development is shifted to the importing application and away from the exporting application.”

The SEEBIM approach certainly presents us with an alternative way of looking at the code-checking problem. It takes away the onus of creating a model properly for code-checking—similar to how a model needs to be created carefully for energy analysis, otherwise it won’t work properly—away from the model-authoring application and places it on the model-checking application, which will intelligently infer the information it needs from the model. This is by no means an easy computational problem, and I am looking forward to seeing how the SEEBIM project evolves.

Conclusions

When it comes to automated code-checking, the effort that started it all—Singapore’s CORENET ePlanCheck system—seems to have been long discontinued. In fact, what came up most when I searched for it—trying various possible keywords—was my own 2005 article (illegally reproduced, I should add; the official archived article is available for purchase here.) Needless to say, it wasn’t working the way it was envisioned, and it was likely that this was because it was ahead of its times—BIM had not yet firmly established in the AEC industry at that time.

Well, we have BIM now, and an increasing number of proposed building designs are being modeled in BIM rather than drawn in CAD, which, in theory, should make automated code-checking easier. While there hasn’t been as much progress in this area since I last wrote about it 18 months ago, the momentum seems to be finally picking up. In addition to the range of commercial solutions described in this article—each with a different approach to the problem—and promising research efforts like SEEBIM, I also learned of some additional efforts that are still under development and not yet ready to go public. I hope when I revisit the topic of automated code checking again, I will have more to discuss, not only in terms of technology solutions but also in terms of implementation by regulatory agencies. Because, ultimately, that is where we need to go.

About the Author

Lachmi Khemlani is founder and editor of AECbytes. She has a Ph.D. in Architecture from UC Berkeley, specializing in intelligent building modeling, and consults and writes on AEC technology. She can be reached at lachmi@aecbytes.com.


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