Publications / 2012 Proceedings of the 29th ISARC, Eindhoven, Netherlands

Cost Effective Sensors for Automated Progress Measurement and Management (APMM)

Youngsoo Jung, Jiwon Ha, Taehwan Ju, Seunghee Kang

Purpose ‘Progress’ is the most often used indicator in construction project management. Nevertheless, excessive man-agement efforts to collect and analyze detailed data have been highlighted as a major barrier for advanced progress management techniques for construction projects. Even though the advent of data acquisition technologies (DATs) pro-vides for automated manipulation of these requirements, previous research efforts have mainly focused on a specific DAT or on the limited construction tasks. In order to effectively utilize DATs for construction projects, a comprehensive approach is desirable, possibly including every single work item within the automated system. The purpose of this paper is to propose such a methodology for integrated utilization of DATs for repeated applications to multiple work items. Method For the purpose of selecting the most adequate DATs for the most frequent patterns of automated data acquisi-tion methods, we first evaluated a comprehensive evaluation of entire work items for a case-project. The criteria for this selection process are modified and simplified based on the algorithm developed by Kang and Jung. Secondly, DAT can-didates for most frequent data acquisition patterns were then systematically examined in order to maximize the benefits of utilizing DATs for construction progress measurement. Results & Discussion We found that the most promising area for automated progress measurement and management (APMM) is to deploy ‘simplified and low-cost sensors’ for moni-toring the ‘entrance and exit’ of ‘labors’ into a locator of ‘floor (story)’ level for a building construction. The rationale, tech-niques, and implications of the proposed methodology are illustrated by a case-project. Recommendations for future research are also discussed.

Keywords: data acquisition technology (DAT), automated progress measurement, sensor, scheduling