An application of metadata-based image retrieval system for facility management

Jong Won Ma, Thomas Czerniawski, Fernanda Leite

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

For facility management, photography is an efficient and accurate method of recording the physical state of infrastructure. However, without an effective organizational scheme, the difficulty of retrieving relevant photos from historical databases can become overly burdensome for highly complex or long-lived assets. To make strategic decisions, it is crucial to retrieve the right information from a plurality of sources in a timely manner. The main objective of this paper is to present a method for organizing and retrieving photos from massive facility management photo databases using photo-metadata: photographed location, camera perspective, and image semantic content information. Indoor localization experiments were performed using Bluetooth technology to infer the location information. Perspective is inferred from the device's on-board inertial measurement unit (IMU). Image semantic content is inferred using a Convolutional Neural Network (CNN)-based deep learning algorithm. Fusing these three features, seven query options were provided for the user when retrieving images. Leveraging Building Information Modeling (BIM) as a process and Geographic Information Systems (GIS) as a framework, this paper also envisions a federated information management by connecting 2D and 3D facility assets with our real-world map which can be smoothly bridged with our image retrieval system. The realization of the integrated application with BIM and GIS is significantly beneficial for the facility management domain by advancing the understanding of projects in a broader view with a federated data platform. In this research, the framework is illustrated with 21 institutional buildings within the University of Texas at Austin's main campus, and the authors conclude that the proposed metadata-based image retrieval system can ultimately enhance the better-informed decision-making process through rapid information retrieval.

Original languageEnglish (US)
Article number101417
JournalAdvanced Engineering Informatics
Volume50
DOIs
StatePublished - Oct 2021

Keywords

  • Bluetooth
  • Building Information Model
  • Facility management
  • Geographical Information System
  • Image retrieval system
  • Indoor localization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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