Towards
an Intelligent Jobsite – Use of Advanced Sensing Technologies on Construction
Jobsites and Industrial Facilities
Funding Agency: King Abdulaziz City of
Science and Technology (KACST)
Funding Program: National Science Technology and Innovation Program,
Forth Cycle (Grant # 1652)
Duration: 24 Months (March 2012 - March 2014)
Budget: SAR 1,135,700 (US$ 302,000 Approx.)
Role and Current Status: Active from March 2012 (Role: Principal
Investigator)
Co-Investigators: Dr. Mohammad Hassanain,
ARE, KFUPM, Dr. Hosam
Rowaihy, COE, KFUPM
Consultants: Dr. William
J. O'Brien, The University of Texas at Austin, Dr. Jie Gong, Southern Illinois
University, Edwardsville
Statement of Work
The project is mainly a technology transfer project and focuses on
comprehensive jobsite instrumentation using a range of field sensing tools.
Publications
Siddiqui, M.K. (Under Preparation) ".." to be submitted to the
Journal of Computing in Civil Engineering, ASCE
Developing
Quantitative Quality Measures for Network Based Schedules
Funding Agency: King Fahd University of Petroleum and
Minerals (KFUPM)
Funding Program: Internal Grant # IN 101021
Duration: 12 Months (March 2011 - March 2012)
Budget: SAR 58000 (US$ 15,000 Approx.)
Role and Current Status: Active (Role: Principal Investigator)
Co-Investigator: Mr. Mohammad Ali Khan, PYP, KFUPM,
Consultant: Dr. Christine Julien, The University of Texas at Austin
Statement of Work:
This project aims to develop predictive quality measures for network based
schedules. The initial motivation of the research was from the Centrality
measures from the Social Network Analysis domain. Two quality measures
(inspired by Betweeness Centrality) have been
developed for identification of scheduling inefficiencies that can result in
creation of new critical paths and increased project duration. The measure rely on the basic scheduling data and are valid in
the absence of probabilistic data for schedule activities. A third measure
has been developed based on EigenValue Centrality
to identify sub-critical chains within the larger network of activities. A
software add-on has been implemented in MS Project to facilitate the
computations for a large set of schedules.
Publications
Khan, M.A. and Siddiqui,
M. K. (2010) “Quantitative Assessment of Network Based Schedules”
Proceedings of ICCCBE 2010, Nottingham, UK, p. 273
Siddiqui, M.K.and
Khan, M.A. (under preparation) "Predictive Quality Measures for
Construction Schedules" to be submitted to the Journal of Construction
Engineering and Management, ASCE
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