JeeWoong Park

Development and Evaluation of a Probabilistic Local Search Algorithm for Complex Dynamic Indoor Construction Sites

AbstractThe nature of an indoor construction site is dynamic and complex. This characteristic becomes even more evident when a multitude of interactions among workers, equipment, and materials exis...

Self-corrective knowledge-based hybrid tracking system using BIM and multimodal sensors

We propose a self-corrective real-time tracking system using a hybrid approach with BLE, motion sensors, and BIM.A full-site construction test was conducted to validate the developed hybrid tracking system.The proposed hybrid tracking system presented a way to compensate for the weakness of each system component.The system components show positive effects through the interaction by reducing tracking errors up to 42%. Researchers have recently devoted considerable attention to acquiring location awareness of assets. They have explored various technologies, such as video cameras, radio signal strength indicator-based sensors, and motion sensors, in the development of tracking systems. However, each system presents unique drawbacks especially when applied in complex indoor construction environments; this paper classifies them into two categories: absolute tracking and relative tracking. By understanding the nature of problems in each tracking category, this research develops a novel tracking methodology that uses knowledge of the strengths and weaknesses of various components used in the proposed tracking system. This paper presents the development of a hybrid-tracking system that integrates Bluetooth Low Energy (BLE) technology, motion sensors, and Building Information Model (BIM). The hypothesis tested through this integration was whether such knowledge-based integration could provide a method that can correct errors found in each of the used sensing technologies and thereby improve the reliability of the tracking system. Field experimental trials were conducted in a full-scale indoor construction site to assess the performance of individual components and the integrated system. The results indicated that the addition of map knowledge from a BIM model showed the capability of correcting improbable movements. Furthermore, the knowledge-based decision making process demonstrated its capability to make positive interaction by reducing the positioning errors by 42% on average. In sum, the proposed hybrid-tracking system presented a novel method to compensate for the weakness of each system component and thus achieve a more accurate and precise tracking in dynamic and complex indoor construction sites.

Performance Tests for Automatic 3D Geometric Data Registration Technique for Progressive As-Built Construction Site Modeling

This study aims to eliminate the labor-intensive target installation process and its associated costs and other issues commonly caused from the current practices of laser based as-built data collection and modeling process. In this study, a laser scan system was utilized with corresponding texture data simultaneously obtained from a digital camera. Based on identified common features in the texture data, an optimized transformation matrix for the point clouds is generated, then the point clouds are registered without using any physical external target. The proposed method was tested at an on-going building construction project. The interrelationships among registration speed, registered accuracy, and size of overlapping area were examined. The field experimental results demonstrate that the proposed target-free geometric data registration method can significantly reduce the registration time without compromising the registration accuracy; thus simplifying and promoting the current laser scanning and registration processes for progressive as-built modeling of construction projects.

Rapid Dynamic Target Surface Modeling for Crane Operation Using Hybrid LADAR System

In order to assist crane operators in rapidly perceiving 3D working environments at dynamic construction sites, an automated rapid 3D workspace modeling method is proposed in this paper. A custom-designed laser scanner system was utilized to collect point cloud data; multiple video camera arrays were used to quickly recognize and track the dynamic objects such as a crane boom. The dynamic target object’s point clouds were separately updated by a smart scan method. At the same time, the point cloud data of previously scanned static work environments were merged to the dynamic scan data. The raw point cloud from extracted target areas was rapidly converted into a 3D surface model using the convex hull algorithm after a process of downsizing the raw data to increase the data processing speed. The performance of the proposed method was tested at a steel frame building construction site. Both the generated dynamic target’s surface models and the point cloud of static surroundings were wirelessly presented to a remote crane operator. The field test results demonstrated that the proposed rapid dynamic target modeling method would significantly improve the crane operation productivity and safety by distinguishing a dynamic surface model being controlled by the operator from the point cloud of existing static environment in 3D views.

Mobile Proximity Sensing Technologies for Personnel and Equipment Safety in Work Zones

This paper introduces a new proximity alarming technology for roadway work zones. Roadway work zones are dynamic in nature and offer workers with limited work space, contributing to dangerous work environments for construction workers who are constructing and maintaining the infrastructure. Hazardous proximity situations can be encountered especially when the ground workers operate in close proximity to heavy construction equipment. Past research effort has been made in aiming at providing proximity sensing technologies for construction workers. These technologies, however, still have limitations that defer extensive deployment, which include accuracy, cost, required hardware, and ease of use. This study focuses on creating and evaluating a feasible technology that overcomes the drawbacks found in other technologies. Using Bluetooth sensing technology, a proximity detection and alert system was created. Experimental results demonstrate the created system’s ability to provide alerts to equipment operators and pedestrian workers at pre-calibrated distance in real-time. The proximity detection and alert device demonstrated its capabilities to provide, with an appropriate alarm, an additional layer of hazard avoidance to pedestrian workers in roadway work zone environments.

Scaffolding Modelling for Real-Time Monitoring using a Strain Sensing Approach

Scaffolding structures are important as a temporary structural element that are used to support workers, equipment, and materials during construction activities. Although 65% of construction workers work on scaffolding structures and often are exposed to safety hazards, the current method of monitoring scaffold structures still is premature. As an example of practices set by the U.S. Occupational Safety and Health Administration, a knowledgeable and experienced individual conducts a visual and labor-intensive inspection. However, one difficulty in conducting structural analysis of a scaffolding structure involves its boundary conditions and material design parameters, which vary depending upon loading conditions. This research explored a new method to accurately model the boundary conditions and design parameters of a scaffolding structure in real time by using wireless strain sensors. An Internet of Things (IoT) opensource Arduino module was used to develop wireless strain sensors to acquire strain data directly from a scaffolding structure. The strain data were transmitted to a finite element method (FEM) model, which was used to estimate the real-time structural behavior of a scaffold. A model-updating technique was used to improve the synchronizing accuracy between the FEM model (i.e., the cyber model) and the actual scaffold. The test results indicated that the proposed synchronizing method described the realtime structural behavior of the scaffold accurately, especially for modelling the boundary conditions and design parameters. The outcomes of this paper are expected to foster the use of wireless sensing technology for safety monitoring of temporary structures and to offer the potential of improving construction safety by preventing the collapse of temporary structures.

Analytic Hierarchical Procedure and Economic Analysis of Pneumatic Pavement Crack Preparation Devices

Various approaches have been used in crack preparations and each of the approaches has advantages and disadvantages. Although the routing method has been widely used and seems to be the best approach among the approaches, it is not a complete solution for crack preparation. This paper compares and evaluates a pneumatic crack cleaning device (CCD) developed by Robotics and Intelligent Construction Automation group at Georgia Tech, over existing devices. Surveys were conducted to discover factors that affect the performance of crack/joint preparation work. Then, data for such information were collected via field tests for devices such as router, heat lancer, air blower and CCD. Performed field test results and follow-up interviews demonstrated that the utilization of CCD has potential to offer improvements in productivity, safety, and maintenance cost. An analytic hierarchical procedure (AHP) and economic analyses were conducted. The AHP analysis considered three factors including safety, quality and productivity while the economic analyses examined the alternatives in various ways. The results indicated that the CCD was ranked first and second for the AHP analysis and economic analysis, respectively. In conclusion, the field tests and results revealed that the utilization of CCD achieved satisfactorily in performance, quality, safety and control, and showed that it has high potential in crack cleaning practice.