Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2020-2021).

The goal of this project is to improve the safety, efficiency, and accountability of large construction projects. Such projects are very complex, involving expensive heavy equipment and human resources, and typically very difficult to manage. We propose to design and develop a decision-support system that helps the management through automated safety alerts, performance metrics, and record keeping. The system takes as input data from internet-connected sensors, including cameras, deployed on the construction sites. With the help of domain experts from construction companies and GreenOwl, we develop algorithms for equipment, human, and event detection for use specifically in the construction domain. Our proposed system is a one-of-its-kind application of cutting edge machine learning to the area of construction projects. The record keeping feature of this system will also contribute indirectly to deter safety protocol violations, corruption, and inefficiencies in large-scale construction projects.