NIBU: a new approach to representing and analysing interior utility networks within 3D geo-information systems
Publication Type
Original research
Authors
  • Ihab H. Hijazi
  • Zlatanova, Sisi
  • Ehlers, Manfred
  • Hijazi, Ihab
  • Zlatanova, Sisi
  • Ehlers, Manfred
  • Hijazi, Ihab Hamzi
  • Ehlers, Manfred
  • Zlatanova, Sisi

Facility management departments' responsibilities include monitoring and maintenance of building infrastructure, such as water, gas or electricity. Very often these tasks are completed using paper maps, which make integrated analysis of networks challenging. Ability to consider interior network structure and provide semantic and connectivity information supporting the required analysis operations are thus crucial.

This paper presents an approach relying on Building Information Model (BIM) as a data source for obtaining information about interior utilities. The semantic and connectivity information of BIM is mapped onto a new model called Network for Interior Building Utilities (NIBU). NIBU is based on the semantic categorisation of utilities, and the spatial functions that have to be performed. Three scenarios (‘maintenance operation’, ‘emergency response’ and ‘inspection operation’) are developed to test the proposed approach.

The model and its functions are implemented in spatial DBMS. The model is populated directly from a BIM server applying an Industrial Foundation Class (IFC) parser developed in-house. Five analysis functions are implemented to support spatial operations: trace upstream, trace downstream, find ancestors, find source and find disconnected. The investigation proves that BIM provides both the required semantics and attributes, and connectivity information that can facilitate analysis of interior utility networks. NIBU provides a simple yet flexible way to manage interior network information, which can be integrated into Digital Earth.

Journal
Title
International Journal of Digital Earth
Publisher
Taylor & Francis Group
Publisher Country
Palestine
Indexing
Thomson Reuters
Impact Factor
2.762
Publication Type
Prtinted only
Volume
5
Year
2012
Pages
22-42