An application of metadata-based image retrieval system for facility management |
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| Affiliation: | 1. Construction Engineering and Project Management Program, Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St. Stop C1752, Austin, TX 78712-1094, United States;2. Del E. Webb School of Construction, School of Sustainable Engineering and the Built Environment, Ira A. Fulton Schools of Engineering, Arizona State University, 660 S College Ave, Tempe, AZ 85281, United States;3. John A. Focht Centennial Teaching Fellowship in Civil Engineering, Construction Engineering and Project Management Program, Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St. Stop C1752, Austin, TX 78712-1094, United States;1. Laboratory for Artificial Intelligence in Design, Hong Kong, China;2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China;1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, PR China;2. Beijing Institute of Electronic System Engineering, Beijing, PR China;3. School of Economics and Management, University of the Chinese Academy of Sciences, Beijing, PR China;4. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, PR China;5. HKU-ZIRI Lab for Physical Internet, Dept. of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China;1. College of Engineering and Technology, Southwest University, Chongqing 400715, China;2. International R & D Center for New Technologies of Smart Grid and Equipment, Southwest University, Chongqing 400715, China;1. School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China;2. Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China;3. Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China;4. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China |
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| 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. |
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| Keywords: | Facility management Image retrieval system Indoor localization Bluetooth Building Information Model Geographical Information System |
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