Knowledge-Based Simulation Modeling of Construction Fleet Operations Using Multimodal-Process Data Mining

AbstractIn order to develop a realistic simulation model, it is critical to provide the model with factual input data based on the interactions and events that take place between real entities. However, the existing trend in simulation of construction fleet activities is based on estimating input parameters such as activity durations using expert judgments and assumptions. Not only may such estimations not be precise, but project dynamics can influence model parameters beyond expectation. Therefore, the simulation model may not be a proper and reliable representation of the real engineering system. In order to alleviate these issues and improve the current practice of construction simulation, a thorough approach is needed that enables the integration of field data into simulation modeling and systematic refinement of the resulting models. This paper describes the latest efforts by authors to design and test a novel methodology for multimodal-process data capturing, fusion, and mining that provides a solid...

[1]  Carlos H. Caldas,et al.  Methodology for Automating the Identification and Localization of Construction Components on Industrial Projects , 2009 .

[2]  Jerry Banks,et al.  Handbook of simulation - principles, methodology, advances, applications, and practice , 1998, A Wiley-Interscience publication.

[3]  Leslie Rutkowski.  Clustering for data mining: A data recovery approach , 2007 .

[4]  Lucio Soibelman,et al.  Data Preparation Process for Construction Knowledge Generation through Knowledge Discovery in Databases , 2002 .

[5]  Patrick Charpentier,et al.  Generation of an adaptive simulation driven by product trajectories , 2012, J. Intell. Manuf..

[6]  Casey Cooper,et al.  Real-Time Simulation for Look-Ahead Scheduling of Heavy Construction Projects , 2009 .

[7]  Carlos H. Caldas,et al.  Using Global Positioning System to Improve Materials-Locating Processes on Industrial Projects , 2006 .

[8]  Simaan M. AbouRizk,et al.  Bayesian Updating Application into Simulation in the North Edmonton Sanitary Trunk Tunnel Project , 2006 .

[9]  James H. Garrett,et al.  Web-Vacuum: Web-Based Environment for Automated Assessment of Civil Infrastructure Data , 2005 .

[10]  Soon-Wook Kwon,et al.  A Gate Sensor for Construction Logistics , 2008 .

[11]  J. Banks,et al.  Handbook of Simulation , 1998 .

[12]  Ming Lu,et al.  SIMPLIFIED DISCRETE-EVENT SIMULATION APPROACH FOR CONSTRUCTION SIMULATION , 2003 .

[13]  Ronie Navon,et al.  Automated project performance control of construction projects , 2005 .

[14]  Wayne J. Davis,et al.  On‐Line Simulation: Need and Evolving Research Requirements , 2007 .

[15]  Boris Mirkin,et al.  Clustering For Data Mining: A Data Recovery Approach (Chapman & Hall/Crc Computer Science) , 2005 .

[16]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[17]  Brenda McCabe,et al.  Vision-based recognition of dirt loading cycles in construction sites , 2012 .

[18]  Julio C. Martinez,et al.  Stroboscope: State and resource based simulation of construction processes. , 1996 .

[19]  Qiang Ling.  How Many Low-Precision Sensors are Enough for Reliable Detection? , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[20]  S. C. Mathewson,et al.  The Application of Program Generator Software and Its Extensions to Discrete Event Simulation Modeling , 1984 .

[21]  Photios G. Ioannou,et al.  General purpose simulation with Stroboscope , 1994, Proceedings of Winter Simulation Conference.

[22]  Pavel Berkhin,et al.  A Survey of Clustering Data Mining Techniques , 2006, Grouping Multidimensional Data.

[23]  Amir H. Behzadan,et al.  An integrated data collection and analysis framework for remote monitoring and planning of construction operations , 2012, Adv. Eng. Informatics.

[24]  Feniosky Peña-Mora,et al.  Application of dimension reduction techniques for motion recognition: Construction worker behavior monitoring , 2011 .

[25]  Simaan M. AbouRizk,et al.  Simphony: an environment for building special purpose construction simulation tools , 1999, WSC '99.

[26]  Jie Gong,et al.  Computer Vision-Based Video Interpretation Model for Automated Productivity Analysis of Construction Operations , 2010 .

[27]  George E. Heidorn,et al.  English as a very high level language for simulation programming , 1974, SIGPLAN Symposium on Very High Level Languages.

[28]  Gregory Piatetsky-Shapiro,et al.  Advances in Knowledge Discovery and Data Mining , 2004, Lecture Notes in Computer Science.

[29]  Bernard J. Schroer,et al.  An expert manufacturing simulation system , 1987, Simul..

[30]  Richard A. Wysk,et al.  Automatic simulation model generation for simulation-based, real-time shop floor control , 2001, Comput. Ind..

[31]  Yongbin Yuan,et al.  A flexible simulation model generator , 1993 .

[32]  Anu Pradhan,et al.  A taxonomy of reasoning mechanisms and data synchronization framework for road excavation productivity monitoring , 2012, Adv. Eng. Informatics.

[33]  Photios G. Ioannou,et al.  General-purpose systems for effective construction simulation , 1999 .

[34]  Ann Lehman,et al.  JMP start statistics : a guide to statistics and data analysis using JMP , 2012 .

[35]  Hubo Cai,et al.  A Framework of RFID and GPS for Tracking Construction Site Dynamics , 2012 .

[36]  Govindan Kannan,et al.  DEVELOPMENT OF AN EXPERIENCE DATABASE FOR TRUCK LOADING OPERATIONS , 2000 .

[37]  Ioannis K. Brilakis,et al.  Automated vision tracking of project related entities , 2011, Adv. Eng. Informatics.

[38]  Chimay J. Anumba,et al.  Ubiquitous location tracking for context-specific information delivery on construction sites , 2008 .

[39]  Ioannis Brilakis,et al.  Detection of Construction Workers in Video Frames for Automatic Initialization of Vision Trackers , 2012 .

[40]  Carl T. Haas,et al.  Reliability-Based Hybrid Data Fusion Method for Adaptive Location Estimation in Construction , 2012 .

[41]  David J. C. MacKay,et al.  Information-Based Objective Functions for Active Data Selection , 1992, Neural Computation.

[42]  Burcu Akinci,et al.  A formalism for utilization of sensor systems and integrated project models for active construction quality control , 2006 .

[43]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[44]  Zhongke Shi,et al.  Tracking multiple workers on construction sites using video cameras , 2010, Adv. Eng. Informatics.

[45]  Jingsheng Shi,et al.  Automated Construction‐Simulation Optimization , 1994 .