Internet-of-things (IoT)-based Data Collection and Analytics for Onsite Scaffolding Project Management

Scaffolding, as a type of temporary structure on construction sites, provides access for trades to certain areas for performing construction activities. Depending on project sizes, the budget for scaffolding can account for a substantial amount of the total direct work budget. Failure to the management of scaffolding activities can result in cost overrun and schedule delays in the projects. Meanwhile, scaffolding management is challenging by its nature, e.g., ad-hoc trivial daily activities with various material components consumed at different locations. This makes scaffolding management difficult, from tracking ongoing activities and material, to well utilize the tracked information for project management. To improve the current industry practice of scaffolding management, timely and accurate data acquisition mechanisms are necessary to record scaffolding data to further form productivity metrics for project management purposes. Therefore, this research project intends to develop a data-driven framework for onsite scaffolding data acquisition and utilization of analytics to provide decision support information for project management. The research team at the University of New Brunswick will collaborate with the Hinton Scaffolding Solutions (Ontario, Canada) to develop Internet-of-things (IoT)-based solutions that incorporate machine learning and statistical methods to form productivity metrics for project earned value analysis (EVA).

Faculty Supervisor:

Zhen Lei

Student:

Partner:

Hinton Scaffold Solutions

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of New Brunswick

Program: