Title

An Integrated Data Collection And Analysis Framework For Remote Monitoring And Planning Of Construction Operations

Keywords

Construction; Control; Data collection; Decision support; Simulation; Visualization

Abstract

Recent advances in data collection and operations analysis techniques have facilitated the process of designing, analyzing, planning, and controlling of engineering processes. Mathematical tools such as graphical models, scheduling techniques, operations research, and simulation have enabled engineers to create models that represent activities, resources, and the environment under which a project is taking place. Traditionally, most simulation paradigms use static or historical data to create computer interpretable representations of real engineering systems. The suitability of this approach for modeling construction operations, however, has always been a challenge since most construction projects are unique in nature as every project is different in design, specifications, methods, and standards. Due to the dynamic nature and complexity of most construction operations, there is a significant need for a methodology that combines the capabilities of traditional modeling of engineering systems and real time field data collection. This paper presents the requirements and applicability of a data-driven modeling framework capable of collecting and manipulating real time field data from construction equipment, creating dynamic 3D visualizations of ongoing engineering activities, and updating the contents of a discrete event simulation model representing the real engineering system. The developed framework can be adopted for use by project decision-makers for short-term project planning and control since the resulting simulation and visualization are completely based on the latest status of project entities. © 2012 Elsevier Ltd. All rights reserved.

Publication Date

10-1-2012

Publication Title

Advanced Engineering Informatics

Volume

26

Issue

4

Number of Pages

749-761

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.aei.2012.04.004

Socpus ID

84867902111 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84867902111

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