Using BIM Geometric Properties for BLE-based Indoor Location Tracking

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1 Using BIM Geometric Properties for BLE-based Indoor Location Tracking JeeWoong Park a, Kyungki Kim b, Yong K. Cho c, * a School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA , USA address: jpark463@gatech.edu b School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA , USA address: kkim369@gatech.edu c School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA , USA address: yong.cho@ce.gatech.edu Abstract The benefits of location awareness of construction resources have been recognized by recent research work. Potentially identified areas include general construction management process, safety, productivity, and material tracking. Despite industrial and academic attempts in this domain, accurate and practical location tracking has not been achieved in construction due to several drawbacks. The limitations include the unreliable performance of sensors, heavy tracking sensor infrastructures, complex occlusions and obstructions, and lack of active utilization of project information in Building Information Model (BIM). Especially, rich information in BIM has been used mainly for visualization. This research introduces an approach that utilizes geometric information of BIM to assist in complex indoor location tracking. The research processes are 1) to define certain geometric constraint objects, 2) to identify required geometric properties of building components, 3) to create tools to extract such information from a BIM model, and 4) to create algorithms to use the extracted information to improve location tracking. A prototype system has been developed and tested in real-time at the entire floor of an indoor environment. The test result showed successful implementation of the integration of BIM s geometric information with BLE-based tracking system. It showed the positive effect of the BIM s geometric information on detecting incorrect movement and improving the position estimation utilizing geometric constraints. Keywords: Bluetooth, BIM, Construction management, Tracking 1

2 1. Introduction 1.1 Indoor tracking The benefits of location awareness of construction resources have been recognized by recent research work. Potentially identified areas include general construction management process, safety, productivity, and material tracking (Cho et al., 2010; Kimoto et al., 2005; Lu et al., 2007). In complex construction projects, locational awareness about construction resources (such as workers, material, and equipment) can lead to improved management of various construction-related issues. Construction resources can be tracked for effective construction management (Cho et al., 2010; Construction Industry Institute, 2008; Lu et al., 2007). Available location information allows immediate sharing of project information pertinent to relevant stakeholders (Behzadan et al., 2008). In addition, construction site safety can be improved based on the real-time locational information (Cheng et al., 2011). Realizing the potential benefits, many research studies and industry applications have attempted to acquire locations of construction resources in real-time, but there exist many challenges in the perspective of both practicality and technicality. Especially, obtaining locational awareness about resources in an indoor environment is considered as highly beneficial but challenging. In the last decades, extensive research has been conducted for tracking an object in indoor applications, utilizing various sensing technologies, including GPS, RFID, Wireless Local Area Network (WLAN), Ultra Wideband (UWB), infrared (IR), ultrasound, Bluetooth, and motion sensors. GPS, as one of the most prevailing tracking technologies cannot be used in the indoor environment due to the signal s inability to penetrate into building shells. Accurate sensors, such as UWB, have been studied by many researchers; however, this technology also still struggles in complex indoor environments due to its own limitations including complex system requirement, line of sight, cost, and deployment sensitivity. Due to these challenges posed by complex indoor environments, few of them have acquired an acceptable level of accuracy and practicality for certain indoor tracking applications in construction. Bluetooth Low Energy (BLE) technology is a relatively new technology that has been introduced since This technology offers many advantages over the conventional Bluetooth technology; they include reduced power consumption rates and low cost, which are the key factors in the practical perspectives. For this reason, this study utilizes the BLE technology to develop a feasible indoor tracking system. 1.2 Use of BIM in tracking Existing tracking approaches do not actively use rich project information in Building 2

3 Information Model (BIM). Recent research work discussed in (Fang et al., 2016), used BIM only for visualization without making contextual interaction with the BIM data. While BIM can provide valuable information to improve the accuracy of location tracking and also assist the interpretation of the tracking results, most of the existing approaches do not use BIM beyond visualization of the construction site and resource locations. Despite the active research effort in BIM, it has not been properly explored with the indoor tracking domain. Due to these drawbacks, acquiring locational awareness for indoor construction is still limited, and the performance of indoor tracking systems often lead to unreliable results. This paper introduces an approach that utilizes the BLE technology for tracking component as well as actively uses rich project information from BIM to enable accurate indoor location tracking. 2. System Architecture The objective of this research was to develop a BLE-based tracking system that integrates and utilizes geometric information from BIM. The developed system is composed of four major components: 1) a mobile BIM solution, 2) location tracking technology, 3) a network system with database, and 4) a software application. Each of these components serves different purposes. They are essential to create an integral solution that enables location-based site data management and seamless communication among project players. Figure 1 provides an overview of the system architecture that this new development is eventually to accomplish. The scope of this paper was to focus on the first two major components above by 1) creating a tool to extract geometric information from a BIM model, 2) mapping such information with indoor tracking information, and 3) improving the tracking quality. 3

4 Fig. 1: System overview 2.1 Use of BIM A BIM model contains data that are valuable and informative in understanding the potential movements of construction resources, such as construction personnel. Such data can form physical boundaries and serve as geometric constraint for a moving target. Before being able to utilize such data, the definitions of these types of data need to be established as well as a tool needs to be created to extract them from a BIM model. Figures 2 and 3 show examples of the geometric constraint that can be found from a BIM model. The edges of a room, walls, and even a wide column are objects that can be considered as geometric constraints. However, for a given as-built BIM model, it can be customized if there is any other unique constraint, such as falling edges, and dangerous areas. Fig. 2: Examples of geometric constraint (column and wall) 4

5 Fig. 3: Examples of geometric constraint (room and door) Figure 4 shows a software tool that has been created by the research team. This tool is used to extract the information of geometric constraint objects from a BIM model. It obtains the properties of the constraint objects, including their coordinates of starting point, ending point, and intermediate point, if necessary. The object data in a BIM model can have different types of properties, and this requires the tool to be sensitive to its implementation especially in calling the right functions to extract desired information. Fig. 4: Extraction tool 2.2 Use of geometric information in tracking The extracted geometric information needs to be outputted into a readable format that can be used in our tracking platform. Two types of file formats, such as a FBX format and a XML format are used in this development. The FBX format is for visualization purpose and the XML formation is for data sharing purpose. Figure 5 displays the process of the geometric data extraction. Since the data is directly from a BIM model, it is automatically matched with 5

6 the map and it creates map knowledge for the tracking system. Fig. 5: Use of geometric data The following pseudo-code illustrates the process of the interaction of position estimation and the geometric constraint conditions. The algorithm described by the pseudo-code rejects a position estimation that violates the geometric constraint conditions and computes a new position estimation that does not violate them. During the entire time of tracking, this interactive computation takes place for each time of position estimation. 6

7 3. Validation and discussion Third floor in Mason building at Georgia Institute of Technology selected as the test bed for our tracking system, and the floor map is shown in Figure 6. The entire are is approximately 29 x 23 meters in a rectangular shape. Traveled path is drawn by a blue line to indicate the ground truth of distance summed to about 83 meters. It was designed to include many numbers of turns to simulate a relatively difficult situation for tracking; this scenario with complex movements creates changes in line of sight conditions for the BLE sensors deployed for the site. The red circles indicate the estimated positions of the test subject. The interactions between the geometric BIM data and the tracking results from the sensors can be found at multiple locations. Toward the middle of the path 1, the estimation was going toward the wall in the north side, but the interaction prevents the estimation from passing through the wall. In addition, the map knowledge prevented the position estimation from moving out of the room near the path 6, withholding the locational errors to minimum. Similar patterns were also seen in the other paths (paths 8 and 13), showing their beneficial interactions. In this particular experiment, errors were calculated as a perpendicular distance from considered estimation to the ground truth path. The maximum error was approximately 1.4 meters and the average error was approximately 0.5 meters. Fig. 6: Testbed and test result 4. Conclusion This study introduced the BLE-based tracking system that integrates and utilizes geometric information from BIM. Geometric object information was first identified, and an extraction tool was developed to acquire such information as a communicable format for the tracking 7

8 system. An interaction algorithm was used to make use of the geometric information together with the tracking estimation by the BLE tracking system. The system was implemented for testing at the entire floor of a building. The test result showed successful implementation of the integration of BIM s geometric information with the BLE-based tracking system. It showed the positive effect of the BIM s geometric information to detect incorrect movement and prevent the position estimation from passing through the geometric constraint (e.g., walls) defined by the BIM model. 5. Acknowledgement This material is based upon work supported by the National Science Foundation (IIP ). Any opinions, findings, and conclusions or recommendations expressed on this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. 6. References Behzadan, A. H., Aziz, Z., Anumba, C. J., and Kamat, V. R. (2008). "Ubiquitous location tracking for context-specific information delivery on construction sites". Automation in Construction, 17(6), doi: /j.autcon Cheng, T., Venugopal, M., Teizer, J., and Vela, P. a. (2011). "Performance evaluation of ultra wideband technology for construction resource location tracking in harsh environments". Automation in Construction, 20(8), doi: /j.autcon Cho, Y. K., Youn, J. H., and Martinez, D. (2010). "Error modeling for an untethered ultra-wideband system for construction indoor asset tracking". Automation in Construction, 19(1), doi: /j.autcon Construction Industry Institute. (2008). "Leveraging Technology to Improve Construction Productivity". Retrieved from veraging-technology-to-improve-construction-productivity Fang, Y., Cho, Y. K., Zhang, S., and Perez, E. (2016). "Case Study of BIM and Cloud Enabled Real-Time RFID Indoor Localization for Construction Management Applications". Journal of Construction Engineering and Management. Kimoto, K., Endo, K., Iwashita, S., and Fujiwara, M. (2005). "The application of PDA as mobile computing system on construction management". Automation in Construction, 14(4), doi: /j.autcon Lu, M., Chen, W., Shen, X., Lam, H.-C., and Liu, J. (2007). "Positioning and tracking construction vehicles in highly dense urban areas and building construction sites". Automation in Construction, 16(5), doi: /j.autcon

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