The purposes of this research are to develop and evaluate a framework that utilizes the integration of commercially-available Radio Frequency Identification (RFID) and a BIM model for real-time resource location tracking within an indoor environment. A focus of this paper is to introduce the framework and explain why building models currently lack the integration of sensor data. The need will be explained with potential applications in construction and facility management. Algorithms to process RFID signals and integrate the generated information in BIM will be presented. Furthermore, to demonstrate the benefits of location tracking technology and its integration in BIM, the paper provides a preliminary demonstration on tracking valuable assets inside buildings in real-time. The preliminary results provided the feasibility of integrating passive RFID with BIM for indoor settings.
Emerging wireless remote sensing technologies offer significant potential in advancing the management of construction processes by providing real-time access to the locations of
workers, materials, and equipment. Unfortunately, little is known regarding the reliability and practical benefits of emerging sensing technology integrated with Building Information Modelling
(BIM) within an indoor building environment. This limitation effectively impedes widespread adoption of sensing technology. This paper introduces and evaluates the framework that integrates
commercially-available Radio Frequency Identification (RFID) technology for real-time, mobile resource location tracking in a BIM model. The need will be explained with potential applications
in construction and facility management. Algorithms to process RFID signals and integrate the generated information in BIM will be presented. Furthermore, to demonstrate the benefits of
location tracking technology and its integration in BIM, the paper provides a preliminary demonstration on tracking valuable assets inside buildings in real-time.
Design-bid-build (DBB) projects are procured by government agencies typically through the competitive bidding process. The decision of the contracting authorities regarding which projects proceed to the bidding stage depends, in part, upon the early estimates of probable cost. Efforts are made to make this estimate as realistic as possible. Irrespective of the estimate of probable cost, the actual project cost is established by the amount of the winning bid and the cost of change orders during construction phase. The change order costs generally are known during the construction phase of the projects. However, the bid cost of projects can be estimated by analyzing the bid data of historical projects. This study will develop a method to predict the future projects’ bid cost of unit price items based on quantities of items. The regression models for various unit price items will be developed by analyzing historical bid data of 151 DBB road projects undertaken by the Clark County Department of Public Works in southern Nevada from 1991 through 2008. The total value of construction was equivalent to $841 million when converted into a June, 2011 base cost. Statistical models were developed to improve the methodologies for estimating bid-item unit pricing and to reduce variances that result in large discrepancies between engineers’ estimates and actual bid-award amounts. These regression models can be used to predict the actual bid cost of the unit price items based on quantity of the unit items.
This paper presents an automated GPS-based method for assessing construction equipment operations productivity. The literature revealed several shortcomings in simulation of construction equipment, for example, the availability of realistic data that supports a simulation framework, and identified the need for integrating real-time field data into simulations. Commercially available GPS-based data logging technology was then evaluated. Analysis methods and rules for monitoring productivity were also discussed. A software interface was created that allowed to analyze and visualize several important parameters towards creating more realistic simulation models. The experimental results showed a productivity assessment method by collecting spatio-temporal data using GPS data logging technology, applied to construction equipment operations, and finally identified and tracked productivity and safety based information for job site layout decision making. This research aids construction project managers in decision making for planning work tasks, hazard identification, and worker training by providing realistic and real-time project equipment operation information.
Information Technology (IT) is an important tool for improving business practices. From the early-1980’s, there has been a huge increase in the adoption of IT in every field. Architecture/ Engineer/ Contractor (A/E/C) community has been a heavy adopter and is significantly more dependent on IT than a decade ago in its daily work. Southern Nevada has been one of the world’s most robust construction markets for the past decade. This study collected data from 28 A/E/C community member firms within Southern Nevada. The study identifies areas where IT is most used and the types of IT used. The research findings will benefit academics by identifying what IT is presently in wide-scale use, and providing an indication of what should presently be integrated into their courses and curriculum.
The vast majority of highway and street projects in the United States are procured by state or local governments through a competitive bidding process. In a competitively bid public project, awarding the contract to the lowest bidder is a predominant practice. A few studies measured the effect of awarding the contract to the lowest bidder on construction cost growth. This paper analyzes a sample of 435 bids on 113 public street projects in Clark County, Nevada, to determine a correlation between a lowest bid price and construction cost growth. The sample included projects completed between 1991 and 2008 and more than $554 million in construction value. The study also determined a correlation between the number of bidders and the deviation of the bid cost from the engineers’ estimate. The study showed no correlation between the lowest bid price and the construction cost growth. It showed that public owners would have received the lowest construction bid price if more bidders had been involved in the bidding process. The study found a strong correlation between the lowest bid price and the final construction cost. Therefore, a regression model was developed to predict the final construction cost of a street project by using the lowest bid price. A validation of the model showed that on average the predicted cost of a project was within 3.51% of the actual construction cost. Other findings included recommendations for future study.
Timely maintenance of highways is very essential to create uninterrupted traffic flow that results in reduced traffic delays and operating costs. Federal as well as State governments are struggling to maintain highways due to budget limitations and lack of decision making tools that help to prioritize the highways that require immediate maintenance. A large number of software has been recently developed based on Geographical Information System (GIS) for the management of traffic, road conditions, and safety data. The majority of the software provides an interface between data and maps. This paper describes the process of developing a GIS-based maintenance management tool that assists in making a reliable and accurate decision regarding road maintenance and management. Factors like traffic counts, pavement conditions, maintenance costs, and alternative roadways available were taken into account in this tool to make a decision regarding prioritization of road maintenance. Synthetic data was used to test and verify the tool. The importance of the tool is discussed and recommendations regarding future research are provided.