The UIA funded project BRISE Vienna uses AI to significantly accelerate the process of issuing building permits. In this project, AI is one of several technologies which are used to inform and support a fully digitized process, linking the planner and the municipal building authority through various digital tools.
In BRISE Vienna, AI is used as a decision support system and as for Background Process Management (Category B and C of the above classification). It helps the staff of the Vienna building authority MA37 to quickly assess, whether a submitted plan for a new building is in line with all existing regulations and requirements. This verification process used to be a manual task and it required review of a range of specific regulatory documents which are specific to the extent of individual sites (e.g. specifying requirements for green roofs, shadowing, terrasses, etc.). These “textual requirements” are part of the formal land-use plan of Vienna and they are attached to it as PDF documents.
The AI-supported verification process in BRISE Vienna automatically analyses all pdf documents linked to a specific site, it then extracts the relevant information in a machine-readable way and provides it as input to the IFC-based digital reference model of the building, against which the submitted plan is being checked.
A textual requirement could read as follows, for example:
“In streets with a breadth of less than 16m, bay windows and protruding loggias may only reach beyond the building line to a maximum of 0,8 m.”
The AI now needs to understand and classify the terms “bay window” and “loggia” and it needs to interpret the additional information “0,8 m” as “MaxDistance”.
To enable the AI to perform these tasks automatically, a manual training of a machine learning program had to be undertaken first. To this end, the staff of MA37, supported by a company specialized on AI, selected and analysed a range of textual requirements and manually defined six categories of requirements with reference to the Vienna building code. The MA37 employees then analysed a sample of 100 PDFs manually and classified the relevant terms into the six categories.
An automated codification of text into numbers was applied to enable statistical learning operations. After this, a range of statistical models were put into place to enable Machine Learning based on the training data provided by MA37.
As a result, the AI is now able to automatically analyse and classify all requirements specified in all legal documents that are linked to the land use plan. From here this information can be transformed into a machine-readable file, which informs a 3D reference model for the site, and it can be made available as decision making support within the verification tool used by the employee of the Vienna building authority. All in all, this saves a significant amount of time throughout the verification process, since all of these steps were undertaken manually before.
A second area of application of AI within BRISE Vienna refers to the automated search of similar law cases.
The authorities of the city of Vienna – like all other municipal authorities – are obliged to take decisions within the boundaries of the current law. In case of a lack of clarity or ambiguiry in the legal provisions, additional documents such as written interpretations must be consulted. These can either stem from past law cases in court or from internal commands of the municipal authority. When analysing and verifying a building application, employees of MA37 often reach the limits of their active knowledge, since the overall number of relevant laws, court decisions and commands is very high. In this situation, in the past, the staff needed to consult the Austrian legal information system RIS (Rechtsinformationssystem), which publishes legal provisions and court decisions. The RIS supports a search based on keywords, but it often provides unsatisfactory results, since the word being searched for was spelled incorrectly or is not contained within the legal text.
This problem was solved by an AI-supported semantic search function. After automatically transferring all documents from PDF to text, a semantic model could be applied which is able to grasp the meaning of a word and relate it to similar or linked terms. With this solution, employees of MA37 can now easily find all relevant past court decisions, law cases, legal provisions, and internal commands in one place. It helps them save a lot of time which they used to spend on researching various data sources with inadequate tools before.
A third application of AI in BRISE Vienna refers to an automated check of submitted documents. In the past, verification staff had to open all submitted documents to check, whether signatures have been provided at the required places. An automated analysis of signatures (based on AI object recognition models) helps prevent this step and shows at one glance, whether all signatures have been provided at the right place in the document. Again, this saves time for the building authority to concentrate on more complex tasks.