Productivity Tracking and Analysis of Earthmoving Operations

Monitoring and control earthmoving operations such as highways and dams construction; require the collection of large amounts of data. Collecting this data manually is time-consuming and it lacks accuracy, so there is a necessity for using automated data collection systems in such operations. Most of nowadays available data acquisition systems are costly back boxes, where the user can not use it based on his/her customised needs. The proposed model allows the customization of the data acquisition system using open source and low cost technologies, in which some sensors are selected to acquire data related to the different factors that could influence the productivity of earthmoving operations. The collected data will be transmitted to a server (cloud) instantly using communication protocols like WiFi. This data is usually collected in a raw format where it has no meaning, so should be processed to have meaningful information that helps in efficiently managing the projects. The proposed model process the collected data using cloud computing to allow higher security and flexibility. The results from data proccing could be retrieved using internet browsers by accessing a secure designated webpage using a user name and password. TBC

Intern: 
Ashraf Salem
Faculty Supervisor: 
Osama Moselhi
Province: 
Quebec
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