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S Taneja, B Akinci,J H Garrett, L Soibelman, B East

BIM-BASED HYBRID INERTIAL POSITIONING FOR FACILITY OPERATIONS SUPPORT

Abstract: Facility operations often require maintenance personnel to locate critical equipment or find the correct shut-off valve in a mechanical room. Mechanical rooms usually have little to no network coverage. Moreover, facilities usually experience a network outage during building emergencies, such as flooding or power outage. Lack of adequate network coverage limits the deployment of network-based positioning and localization solutions in such environments. Hence, there is a need for an infrastructure-free positioning solution that does not require WLAN network. This paper evaluates algorithms that utilize a navigation network created from BIM-based floor plans for correcting inertial positioning data, which is susceptible to drift errors (Gelb 1974). We have built on top of map-matching approaches that have been used for correcting positioning data from GPS by utilizing road network representations in GIS databases (Scott 1994; Spassov 2007). In particular, we have created a navigation network representation of the indoor environments based on the Medial Axis Transform (Taneja et al. 2011b) for implementing two different map-matching algorithms, namely, a weighted geometric matching algorithm and a topological matching algorithm. We have implemented a prototype that acquires data from a commercial Inertial Sensing Unit, performs map-matching calculations on a portable tablet computer and displays the position output on top of a floor plan on the tablet computer. This paper presents the evaluation of the performance of the two map-matching algorithms in field tests carried out in one of the heavily utilized academic facilities in Pittsburgh, PA. Performances of the algorithms have been characterized in terms of horizontal positioning accuracy of corrected position data (in meters).

Keywords: Facility operations, Inertial positioning, Map-matching, Navigation network

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Series: w78:2011 (browse)
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Saurabh Taneja, Burcu Akinci, James H. Garret, Lucio Soibelman, E. William East

Evaluation of Localization Algorithms for WLAN-Based Tracking to Support Facility Management Field Activities

Abstract: Facility management activities often require the capability to track and guide field personnel during routine and corrective maintenance tasks in dense indoor environments and large facilities. For example, during a water leak, a facility maintenance employee might require guidance to the nearest valve in a mechanical room. Such guidance requires accurate localization and tracking of mobile maintenance personnel in the field. The objective of this research study is to evaluate various localization algorithms for WLAN-based tracking of maintenance personnel in terms of accuracy and precision. Accuracy has been defined as the ability of a localization approach to track a person within a certain distance and precision has been defined as the ability to reproduce the required accuracy over time. The research described in this paper builds on the previous work of the authors on static user localization and utilizes the same test bed for evaluating the performance of different algorithms that utilizes WLAN technology to support mobile personnel tracking. The main motivation behind using the same test bed, which is an actively utilized building in Pittsburgh, PA, is to have the same baseline to evaluate the performance of static user localization and mobile user tracking. WLAN technology has been selected as it achieved good results for stationary personnel localization in the previous research work (Taneja et al. 2010). The authors have evaluated deterministic and probabilistic algorithms based on the fingerprinting approach (Bahl and Padmanabhan 2000) for mobile personnel tracking. The reason behind selecting fingerprinting approach is that this approach does not require line-of-sight between localization technology transmitters and mobile receivers, which was identified as a requirement in the previous research work (Taneja et al. 2010). The fingerprinting approach is further augmented by adding several filtering methods (Fox et al. 2003) to evaluate the impact of incorporating the motion characteristics of humans and the layout of the indoor environment on the accuracy and precision of the implemented algorithms. Initial assessment of the results indicate that deterministic algorithms perform better than probabilistic approaches when fingerprint data is limited, and incorporating the motion characteristics of humans and the layout of the indoor environment by implementing filtering methods, increases the accuracy and precision of mobile personnel tracking.

Keywords: Facility Management, Mobile Tracking, Indoor Positioning, WLAN, Fingerprinting

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Series: w78:2010 (browse)
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Z Aziz, CJ Anumba, D Ruikar, PM Carrillo & NM Bouchlaghem

Context Aware Information Delivery for On-Site Construction Operations

Abstract: The information intensive nature of construction projects requires the site personnel to have an on-demand access to project information. Current information delivery methods are primarily static and do not take into account the site personnel's changing context. Delivering information to site staff, based on their context (such as location, time and profile) has the tremendous potential to improve construction productivity. In this paper a prototype application for context-aware information delivery is discussed. The implementation is based on a Pocket-PC platform and makes use of wireless local area networking (WLAN) to capture context parameters. A semantics-based Resource Description Framework Schema (RDFS) is used for both context interpretation and to define construction documents and project task structure. Conclusions are drawn about the possible future impact of context-aware applications for the construction industry.

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Full text: content.pdf (694,920 bytes) (available to registered users only)

Series: w78:2005 (browse)
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Permission to reproduce these papers has been graciously provided by the Technische Universitšt Dresden.


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