Abstract
New computational methods provide means to deduce semantic information from measurements, such as range scans and photographs of building interiors. In this paper, we showcase a method that allows to estimate elements that are not directly observable – ducts and power lines in walls. For this, we combine information, which is deducted by algorithms from the
raw data, with implicit information that is publicly available: technical standards that restrict the placement of powerlines. These requirements define preferred installation zones, which are represented by a rule-based system in the proposed approach.
The approach is structured into the following steps: First, a coarse geometry is extracted from input measurements; i.e. the unstructured, laser-scanned point cloud is transformed into a simplistic building model. Then, visible endpoints of electrical appliances (e.g. sockets, switches) are detected from picture information using machine-learning techniques and a pre-trained
classifier. Afterwards, the positions of installation zones in walls are generated using the rulebased system mentioned above. Finally, a hypothesis of non-visible cable ducts is generated, under the assumption that (i) the real configuration obeys the rules of legal requirements and
standards and (ii) the configuration connects all endpoints using as little as possible resources, i.e. cable length. Results of a first automatic pipeline are discussed.
raw data, with implicit information that is publicly available: technical standards that restrict the placement of powerlines. These requirements define preferred installation zones, which are represented by a rule-based system in the proposed approach.
The approach is structured into the following steps: First, a coarse geometry is extracted from input measurements; i.e. the unstructured, laser-scanned point cloud is transformed into a simplistic building model. Then, visible endpoints of electrical appliances (e.g. sockets, switches) are detected from picture information using machine-learning techniques and a pre-trained
classifier. Afterwards, the positions of installation zones in walls are generated using the rulebased system mentioned above. Finally, a hypothesis of non-visible cable ducts is generated, under the assumption that (i) the real configuration obeys the rules of legal requirements and
standards and (ii) the configuration connects all endpoints using as little as possible resources, i.e. cable length. Results of a first automatic pipeline are discussed.
Original language | English |
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Title of host publication | Places and Technologies 2016 : Conference Proceedings of the 3rd International Academic Conference on Places and Technologies |
Editors | Eva VaništaLazarević, Milena Vukmirović, Aleksandra Krstić-Furundžić, Aleksandra Đukić |
Number of pages | 8 |
Place of Publication | Belgrade |
Publisher | University of Belgrade, Faculty of Architecture |
Publication date | 2016 |
Pages | 77-84 |
ISBN (Electronic) | 978-86-7924-160-3 |
Publication status | Published - 2016 |
Event | Places and Technologies - Beograd, Serbia Duration: 14 Apr 2016 → 15 Apr 2016 http://www.placesandtechnologies.eu/ |
Conference
Conference | Places and Technologies |
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Country/Territory | Serbia |
City | Beograd |
Period | 14/04/2016 → 15/04/2016 |
Internet address |
Keywords
- building information modelling
- semantic enrichment
- geometric enrichment
- as-built BIM
- electrical wiring hypothesis
Artistic research
- No