Large-scale earthmoving activities make up a costly and air-polluting aspect of many construction projects and mining operations, which depend entirely on the use of heavy construction equipment. The long-term jobsites and manufacturing nature of the mining sector has encouraged the application of automated controlling systems, more specifically GPS, to control the earthmoving fleet. Computer vision-based methods are another potential tool to provide real-time information at low-cost and to reduce human error in surface earthmoving sites as relatively clear views can be selected and the equipment offer recognizable targets. Vision-based methods have some advantages over positioning devices as they are not intrusive, provide detailed data about the behaviour of each piece of equipment, and offer reliable documentation for future reviews. This dissertation explains the development of a vision-based system, named server-customer interaction planner (SCIT), to recognize and estimate earth material loading cycles. The SCIT system consists of three main modules: object recognition, tracking, and action recognition. Different object recognition and tracking algorithms were evaluated and modified, and then the ideal methods were used to develop the object recognition and tracking modules. A novel hybrid tracking framework was developed for the SCIT system to track dump trucks in the challenging views found in the loading zones. The object recognition and tracking engines provide spatiotemporal data about the equipment which are then analyzed by the action recognition module to estimate loading cycles. The entire framework was evaluated using videos taken under varying conditions. The results highlight the promising performance of the SCIT system with the hybrid tracking engine, thereby validating the possibility of its practical application.

Large-scale earthmoving activities make up a costly and air-polluting aspect of many construction projects and mining operations, which depend entirely on the use of heavy construction equipment. The long-term jobsites and manufacturing nature of the mining sector has encouraged the application of automated controlling systems, more specifically GPS, to control the earthmoving fleet. Computer vision-based methods are another potential tool to provide real-time information at low-cost and to reduce human error in surface earthmoving sites as relatively clear views can be selected and the equipment offer recognizable targets. Vision-based methods have some advantages over positioning devices as they are not intrusive, provide detailed data about the behaviour of each piece of equipment, and offer reliable documentation for future reviews. This dissertation explains the development of a vision-based system, named server-customer interaction planner (SCIT), to recognize and estimate earth material loading cycles. The SCIT system consists of three main modules: object recognition, tracking, and action recognition. Different object recognition and tracking algorithms were evaluated and modified, and then the ideal methods were used to develop the object recognition and tracking modules. A novel hybrid tracking framework was developed for the SCIT system to track dump trucks in the challenging views found in the loading zones. The object recognition and tracking engines provide spatiotemporal data about the equipment which are then analyzed by the action recognition module to estimate loading cycles. The entire framework was evaluated using videos taken under varying conditions. The results highlight the promising performance of the SCIT system with the hybrid tracking engine, thereby validating the possibility of its practical application.

Automated technologies can be beneficial for collecting data on the condition of pavements. As opposed to a traditional manual survey of the road, automated data collection can provide a safer alternative that is objective, repeatable, and consistent, while traveling at highway speeds. Though the automated method is preferred, it still needs to be reliable enough to accurately model the current pavement performance. The Texas Department of Transportation (TxDOT) initiated a project to allow an independent assessment of the accuracy and repeatability of new automated distress data measurements. In this study, 20 550-ft. pavement sections were tested with automated data collection technologies. The sections were located in Austin and Waco Districts. The accuracy and repeatability was evaluated for cracking and other distress measurements, cross slope measurements, and texture measurements. Known manual methods were used as a reference, and a 3D system developed by TxDOT was compared with three systems of other vendors (Dynatest, Fugro, and Waylink-OSU). With the data provided for the texture and cross slope, an additional investigation was done to evaluate hydroplaning potential. This thesis reports in the latter investigation. / text

Automated data acquisition has revolutionized the reliability of product design in recent years. A noteworthy example is the improvement in the design of aircrafts through field data. This research proposes a similar improvement in the reliability of process design of earthmoving operations through automated field data acquisition. The segment of earthmoving operations addressed in this research constitutes the truck-loader operation. Therefore, the applicability of this research extends to other industries involving truck-operation such as mining, agriculture and forest logging and is closely related to wheel-based earthmoving operations such as scrapers. The context of this research is defined by data collection needed to increase the validity of the results obtained by analysis tools such as simulation, performance measures and graphical representation of variance in an activity's performance, and the relation between operating conditions and the variance in an activity's performance. The automated cycle time data collection is facilitated by instrumented trucks and the collection of information on operating conditions is facilitated by image database and paper forms. The cycle time data and the information on operating conditions are linked together to form the experience database. This research developed methods to extract, quantify and understand the variation in each component of the earthmoving cycle namely, load, haul and return, and dump activities. For the load activity, the simultaneous variation in payload and load time is illustrated through the development of a PLT (PayLoad Time) Map. Among the operating conditions, material type, load area floor, space constraints and shift are investigated. A dynamic normalization process of determining the ratio of actual travel time to expected travel time is developed for the haul and return activities. The length of the haul road, sequence of gear downshifts and shift are investigated for their effect on the travel time. The discussion on the dump activity is presented in a qualitative form due to the lack of data. Each component is integrated within the framework of the experience database. The implementation aspects with respect to developing and using the experience database are also described in detail. The practical relevance of this study is highlighted using an example. / Ph. D.

This on-road field investigation employed, for the first time, a completely automated, trigger-based data collection system capable of evaluating driver performance in an extended duration real-world commercial motor vehicle environment. The complexities associated with the development of the system, both technological and logistical and the necessary modifications to the plan of research are presented herein This study, performed in conjunction with an on-going three year contract with the Federal Highway Administration, examined the use of self-rating of alertness and temporal separation (minimum time-to-collision, minimum headway, and mean headway) as indicators of driver fatigue. Without exception, the regression analyses for both the self-rating of alertness and temporal separation yielded models low in predictive ability; neither metric was found to be a valid indicator of driver fatigue. Various reasons for the failure of self-rating of fatigue as a valid measure are discussed. Dispersion in the data, likely due to extraneous (non-fatigue related) factors (e.g., other drivers) are credited with reducing the sensitivity of the temporal separation indicators. Overall fatigue levels for all temporal separation incidents (those with a time-to-collision equal to or less than four seconds) were found to be significantly higher than for those randomly triggered incidents. On this basis, it is surmised that temporal separation may be a sensitive indicator for time-to-collision values greater than the 4-second criterion employed in this study. Two unexpected relationships in the data are also discussed. A "wall" effect was found to exist for minimum time-to-collision values at 1.9 seconds. That is, none of the participants who participated in this research effort exhibited following behaviors with less than a 1.9-second time-to-collision criterion. In addition, based upon the data collected for this research, anecdotal evidence suggests that commercial motor vehicle operators do not appear to follow the standard progression of events associated with the onset of fatigue. / Ph. D.

Den tekniska utvecklingen har möjliggjort ett mer uppkopplat samhälle genom enklare informationstillgång och mer avancerad informationshantering. Den här framfarten har legat till grund för utveckling av samlingsbegreppet Internet of Things, där automatiserade datainsamlingssystem är betydande för insamling av mer kvantitativa datamängder. Detta har lett till att företag inom flera olika industrier har integrerat tekniken i delar av verksamheten för att samla in en betydande datamängd i syfte att utveckla och förbättra de egna processerna. Intresset och framförallt behovet av den här typen av teknologi finns inom byggindustrin. För ett byggföretag som vill arbeta med digitala lösningar i deras arbete gäller att skapa förståelse för varför den typen av lösning ska användas och hur den kan nyttjas på bästa sätt. Vid implementering och anpassning av en ny teknik är det nödvändigt för företag att identifiera vilka möjligheter och hinder som kan uppstå. Därav är syftet med studien att undersöka möjligheten att samla in realtidsdata genom en automatiserad insamlingsprocess i produktionsfasen hos ett byggföretag. Vidare undersöks hur processen bidrar till kvalitetssäkring och ständiga förbättringar i byggprojekten. Detta för att skapa medvetenhet hos byggföretag om en ny teknik som kan underlätta deras arbete och hindra uppkomst av problem. En fallstudie har genomförts hos byggföretaget JM AB som har en lång erfarenhet av byggprocesser och byggprojekt. För att skapa förståelse kring studiens ämne och slutsatser har en en teoretisk referensram innehållandes teorier om bland annat kvalitetssäkring och datainsamling byggts upp. Genom tio intervjuer med anställda av olika befattningar, två observationer på ett av fallföretagets byggprojekt och en intervju med ett externt företag sammanställdes en empirisk undersökning. På så sätt erhölls insikt i hur fallföretaget arbetar med datainsamlingsprocesser och vilka tekniker som finns på marknaden. Genom analys av fallstudien framkom det tydligt att fallföretaget inte har välutarbetade datainsamlingsprocesser inom flera områden i byggproduktionen. En viktig slutsats i studien är att användandet av ett processinnovationsramverk kan skapa förutsättningar för en effektiv och automatiserad datainsamlingsprocess. Ramverket ger stöd till huruvida en automatisk datainsamlingsprocess är lönsamt samt skapar förståelse kring processen innan den är redo att implementeras. Dessutom möjliggör en automatiserad datainsamlingsprocess kvalitetsförbättringar med hjälp av ett kvalitetskontrollramverk som kan öka kvaliteten genom att reducera problem och lösa dem fortare. Kvalitetskontrollerna blir systematiska och utifrån genererad data kan jämförelser göras för att identifiera defekter så att arbete mot snabbare handlingsåtgärder kan skapas. Utifrån slutsatserna har fyra rekommendationer tagits fram, den första är att använda processinnovationsramverk vid undersökning av en ny automateringsprocess. Den andra är att testa automatiserade datainsamlingsprocesser i mindre projekt för att erhålla ökad förståelse. Den tredje är att systematiskt arbeta med ett kvalitetskontrollramverk utifrån genererad data. Den sista rekommendationen är att använda insamlad data till faktabaserade beslut och sträva mot ständiga förbättringar. / Technological developments have enabled a more connected society with easier access to information that creates opportunities for more advanced information management. This has been the basis for development of the generic term Internet of Things, where automated data collection systems are significant for the collection of quantitative data set. Companies in various industries are embracing the integration of this type of technology in their businesses to generate data that is possessed to improve their processes. The interest and especially the need for this type of technology is huge in the construction industry.   For construction companies that wants to work with digital solutions, it is important to create an understanding of why this type of solution is to be used and how it best can be utilized. In implementation and adaption of a new technology, it is necessary for companies to identify the opportunities and obstacles that may arise. Hence, the purpose of this study is to examine the feasibility of collecting real-time data through an automated collection process in the production phase at a construction company, and how it contributes to quality assurance and continuous improvement in construction projects. In this way, awareness among construction companies of a new technique can facilitate their work and prevent upcoming problems. A case study has been carried out at the construction company JM AB who has a long experience of construction processes. To create an understanding about the study topic and conclusions, a theoretical framework was compiled including theories about quality assurance and data collection. Through ten interviews with employees of different positions, two observations at one of the case company’s construction projects and one interview with an external company, an empirical study was compiled. In this way, insights were obtained into how the case company is working with data collection processes and what techniques that are available on the market. Through analysis of the case study, it crearly appeared that the case company does not have well-developed data collection processes in several areas of the building production. One important conclusion of the study is that the use of a process innovation framework can create conditions for an efficient and automated data collection process. The framework supports whether an automated data collection process is profitable and it creates an understanding of the process prior of its implementation. Another important conclusion is that an automated data collection process allows quality improvements through the help of a quality control framework that can increase the quality by reducing problems and solving them faster. Hence, quality controls become systematic and based on generated data, comparisons can be made to identify defects in order to work systematically toward faster action measures. Based on the findings, four recommendations were developed. The first one is to use process innovation framework for the examination of a new automatic process. The second is to test automated data collection processes into smaller projects to obtain greater understanding. The third is to work systematically on a quality control framework based on generated data. The last recommendation is to use the collected data for fact-based decisions and to strive for continuous improvement.

By using innovative methods, such as the automated transfer of corporate electronic data to National Statistical Institutions, official transport data can be significantly improved in terms of reliability, costs and the burden on respondents. In this paper, we show that the automated compilation of statistical reports is possible and feasible. Based on previous findings, a new method and tool were developed in cooperation with two business partners from the logistics sector in Austria. The results show that the prototype could successfully be implemented at the partner companies. Improved data quality can lead to more reliable analyses in various fields. Compared to actual volumes of investments into transport, the costs of transport statistics are limited. By using the new and innovative data collection techniques, these costs can even be reduced in the long run; at the same time, the risk of bad investments and wrong decisions caused by analyses relying on poor data quality can be reduced. This results in a substantial value for business, research, the economy and the society.

Master of Science / Department of Electrical & Computer Engineering / Steve Warren / Handgrip contractions are a standard exercise modality to evaluate muscular system performance. Most conventional ergometer systems that collect handgrip contraction data are manually controlled, placing a burden on the researcher to guide subject activity while recording the resultant data. Further, post-processing tools for this type of experiment are not standardized within the domain, which requires investigators to process their data with multiple tool sets and often create custom tool sets for that purpose. This can make experimental data difficult to compare and correlate, even within the same research group. This thesis presents updates to a hand-forearm ergometer system that automate the control and data-acquisition processes as well as provide a tool set to post process hand contraction data. The automated system utilizes a LabVIEW virtual instrument as the system centerpiece; it provides the subject/researcher interfaces and coordinates data acquisition from both traditional and new sensors. The tool set also incorporates a collection of MATLAB scripts that allow the investigator to post process these data in a standard way, such as automating the processes of noise floor removal, burst start/stop time identification, and mean/median frequency calculation in electromyograms (EMGs). The tool set has proven to be a viable support resource for experimental studies performed by the Kansas State University Human Exercise Physiology lab that target muscle fatigue in human forearms. Initial data acquired during these tests indicate the viability of the system to acquire consistent and physiologically meaningful data while providing a usable tool set for follow-on data analyses.

Thesis (M.Eng.)--University of Wollongong, School of Electrical, Computer & Telecommunications Engineering. / Typescript. Includes bibliographical references: leaf 143-147.

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009 / The purpose of this project is to develop methods for distribution network power quality' variations monitoring. Power quality (PO) has become a significant issue for both power suppliers and customers. There have been important changes in power system regarding to power quality requirements. "Power quality" is the combination at voltage quality and current quality. The main research problem of the project is to investigate the power quality of a distribution network by selection of proper measurement, applying and developing the existing classic and modern signal conditioning methods for power disturbance's parameters extracting and monitoring. The research objectives are: To study the standard lEC 61000-4-30 requirements. to investigate the common couplings in the distribution network. To identity the points for measurement, to develop MySQL database for the data from the measurement and to develop MATLAB software tor simulation of the network To develop methods based on Fourier transforms for estimation of the parameters of the disturbances. To develop software for the methods implementation, The influence of different loads on power quality disturbances are considered in the distribution network. Points on the network and meters according to the lEC power quality standards are investigated and applied for the CPUT Bellville campus distribution network. The implementation of the power quality monitoring for the CPUT Bellville campus helps the quality of power supply to be improved and the used power to be reduced. MATLAB programs to communicate with the database and calculate the disturbances and power quality parameters are developed.