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Funded Research Projects


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