scholarly journals BIM-based Augmented Reality for Facility Maintenance Management

2021 ◽  
Author(s):  
Hamidreza Alavi ◽  
Nuria Forcada ◽  
Su-Ling Fan ◽  
Wei San
Keyword(s):  
Augmented Reality ◽  
Maintenance Management ◽  
Facility Maintenance

Research for Framework of BIM-Based Platform on Facility Maintenance Management on the Operating Stage in Metro Station

2015 ◽  
Vol 743 ◽  
pp. 702-710 ◽  
Author(s):  
X.Y. Xie ◽  
T.C. Xie
Keyword(s):  
Facility Management ◽  
Maintenance Management ◽  
Metro Station ◽  
Operation Stage ◽  
Exploratory Stage ◽  
Facility Maintenance ◽  
Data Requirements ◽  
Daily Travel ◽  
Operating Stage ◽  
The Ideal

Facility management in metro station is an important content of the operation stage, relates to people's daily travel safety, and needs to be more efficient and reliable. At present, the research and application of BIM in the design and construction stage has made great progress in the domestic, but the research of BIM in operation stage is still in the exploratory stage. Through the investigation, this study analyzed the demand of the facility management in metro station, proposed data requirements to build operation model of a metro station, established a framework of BIM-based platform on facility maintenance management in metro station, and expected to provide a more efficient and reliable digital means for facility management in metro station. The results of this study were applied in a metro station in Shanghai, and obtained the ideal effect.

scholarly journals Facility maintenance management system based on GIS and indoor map

2019 ◽  
Vol 9 (4) ◽  
pp. 3323
Author(s):  
Supattra Puttinaovarat ◽  
Suwat Jutapruet ◽  
Aekarat Saeliw ◽  
Siwipa Pruitikanee ◽  
Jinda Kongcharoen ◽  
...  
Keyword(s):  
Management System ◽  
Web Applications ◽  
System Development ◽  
Model System ◽  
Geospatial Data ◽  
Maintenance Management ◽  
Time Data ◽  
Facility Maintenance ◽  
Development Approach ◽  
Time Limitations

This research presented a system development approach for facility maintenance management system based on GIS and indoor map in the form of web applications that can be used with all devices and no worries about time limitations. The capabilities of GIS, indoor map, and geospatial data visualization help speeding up facility maintenance management process and create benefits to all concerned parties, i.e., users can notify and follow the data of facility errors at the time; or officers in charge can operate quickly because they can access real-time data. Indoor map display makes it easier to access locations or places of damaged facilities. In addition, the data from the model system presented in this research can also be applied to planning and decision-making of executives.

scholarly journals A Review of Embedding Artificial Intelligence in Internet of Things and Building Information Modelling for Healthcare Facility Maintenance Management

2021 ◽  
Vol 11 (2) ◽  
pp. 31
Author(s):  
Mina Sadat Orooje ◽  
Mohammad Mehdi Latifi
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Healthcare Facility ◽  
Facility Management ◽  
Maintenance Management ◽  
Building Information Modelling ◽  
Information Modelling ◽  
Related Data ◽  
Building Information ◽  
Facility Maintenance

Latest innovations in Internet of Things (IoT) technologies as well as the new paradigms in Artificial Intelligence systems are opening up opportunities to create smart computing infrastructures for the Healthcare Facility Management. However, the current scenario of hospital buildings maintenance management is strongly characterized by slow, redundant, and not integrated processes, which lead to loss of money, resources, and time. On the other hand, lack of data and information in as-built digital models considerably limits the potential of Building Information Modelling in Facility Maintenance Management. Consequently, optimization of data collection process and management is required. In this light, this paper presents a review of embedding AI (Artificial Intelligence) in BIM-IoT integration for the process of healthcare Facility Maintenance Management (FMM) in order to conquer the current challenges. The first challenge in front of integrating IoT– BIM, is the lack of information; the second challenge is BIM’s sematic information that has not been able to display indoor conditions’ elements which should be reconsidered; and the third challenge is the data size which is stored in systems as well as the eligibility of individuals to apply the related data. Additionally, some emerging trends in IoT are reviewed such as the combination of Machine Learning and Artificial Intelligence in order to exploit their advantages and complement their limitations, which enable new promising IoT applications.

scholarly journals Performance Study on Natural Marker Detection for Augmented Reality Supported Facility Maintenance

2014 ◽  
Vol 2 (1) ◽  
pp. 23 ◽  
Author(s):  
Christian Koch ◽  
Matthias Neges ◽  
Markus König ◽  
Michael Abramovici
Keyword(s):  
Augmented Reality ◽  
Maintenance Phase ◽  
Indoor Navigation ◽  
Working Environment ◽  
Cycle Period ◽  
Detection Accuracy ◽  
Performance Study ◽  
Lighting Conditions ◽  
Facility Maintenance ◽  
Marker Detection

The operation and maintenance phase is the longest and most expensive life-cycle period of building facilities. Operators need to perform activities to provide a comfortable living and working environment and to upkeep equipment to prevent functionality failures. For that purpose they manually browse, sort and select dispersed and unformatted facility information before actually going on the site. Although some software tools have been introduced, they still spent 50% of the on-site work on inspection target localization and navigation. To improve these manual, time consuming and tedious procedures, the authors previously presented a framework that uses BIM-based Augmented Reality (AR) to support facility maintenance tasks. The proposed workflow contains AR supported activities, namely AR-based indoor navigation and AR-based maintenance instructions. An inherent problem of AR is marker definition and detection. As introduced, indoor natural markers such as exit signs, fire extinguisher location signs, and appliances’ labels were identified to be suitable for both navigation and maintenance instructions. However, small markers, changing lighting conditions, low detection frame rates and accuracies might prevent the proposed approach from being practical. In this paper the performance of natural marker detection will be evaluated under different configurations, varying marker types, marker sizes, camera resolutions and lighting conditions. The detection performance will be measured using pre-defined metrics incorporating detection accuracy, tracking quality, frame rates, and robustness. The result will be a set of recommendations on what configurations are most suitable and practical within the given framework.

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