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Beavers, J E, Moore, J R, Rinehart, R and Schriver, W R (2006) Crane-Related Fatalities in the Construction Industry. Journal of Construction Engineering and Management, 132(09), 901–10.

Kolera, B T and Bernold, L E (2006) Intelligent Utility Locating Tool for Excavators. Journal of Construction Engineering and Management, 132(09), 919–27.

Nuntasunti, S and Bernold, L E (2006) Experimental Assessment of Wireless Construction Technologies. Journal of Construction Engineering and Management, 132(09), 1009–18.

Ozorhon, B, Dikmen, I and Birgonul, M T (2006) Case-Based Reasoning Model for International Market Selection. Journal of Construction Engineering and Management, 132(09), 940–8.

Puddicombe, M S (2006) The Limitations of Planning: The Importance of Learning. Journal of Construction Engineering and Management, 132(09), 949–55.

Shen, L Y, Zhao, Z Y and Drew, D S (2006) Strengths, Weaknesses, Opportunities, and Threats for Foreign-Invested Construction Enterprises: A China Study. Journal of Construction Engineering and Management, 132(09), 966–75.

Sik-wah Fong, P and Chu, L (2006) Exploratory Study of Knowledge Sharing in Contracting Companies: A Sociotechnical Perspective. Journal of Construction Engineering and Management, 132(09), 928–39.

Singh, D and Tiong, R L K (2006) Contractor Selection Criteria: Investigation of Opinions of Singapore Construction Practitioners. Journal of Construction Engineering and Management, 132(09), 998–1008.

Song, J, Haas, C T and Caldas, C H (2006) Tracking the Location of Materials on Construction Job Sites. Journal of Construction Engineering and Management, 132(09), 911–8.

  • Type: Journal Article
  • Keywords: Construction industry; Construction materials; Construction management;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:9(911)
  • Abstract:
    Automated tracking of materials on construction projects has the potential to both improve project performance and enable effortless derivation of project performance indicators. This paper presents an approach by which materials tagged with radio frequency identification (RFID) tags can be automatically identified and tracked on construction sites, without adding to regular site operations. Essentially, this approach leverages automatic reading of tagged materials by field supervisors or materials handling equipment that are equipped with a RFID reader and a global positioning system receiver. To assess the technical feasibility of this approach, a mathematical model has been formulated such that the job site is represented as a grid and the location of materials within the grid is determined by combining proximity reads from a discrete range. Field experiments were conducted using an off-the-shelf RFID technology, and several metrics were developed to quantify the field performance and compare it with the theoretical positional accuracy derived from the discrete formulation.

Tatum, C B, Vorster, M and Klingler, M (2006) Innovations in Earthmoving Equipment: New Forms and Their Evolution. Journal of Construction Engineering and Management, 132(09), 987–97.

Tatum, C B, Vorster, M, Klingler, M G and Paulson, B C (2006) Systems Analysis of Technical Advancement in Earthmoving Equipment. Journal of Construction Engineering and Management, 132(09), 976–86.

Zhang, X (2006) Factor Analysis of Public Clients’ Best-Value Objective in Public–Privately Partnered Infrastructure Projects. Journal of Construction Engineering and Management, 132(09), 956–65.