Automated crack segmentation in close-range building façade inspection images using deep learning techniques

Nowadays, unmanned aerial vehicles (UAVs) are frequently used for periodic visual inspection of building envelopes to detect unsafe conditions or vulnerable damages. Inspection practitioners have to manually examine the large amounts of high-resolution images collected by UAVs to identify anomalies or damages on building facades for reporting and repairs. The computer vision and deep learning technologies have emerged as promising solutions to automate the image-based inspection process.

2020 SDDC: Project Report

The management of society’s waste, once overlooked as a burden to simply dump onto the Earth, has grown in public awareness during the last several decades as critical to sustainable planning. For the 2020 Solar Decathlon Design Competition, we are excited to work with a client that is setting the gold standard for contemporary waste management in our home state of Virginia.

2020 SDDC: Finalist Presentation

In order to provide a holistic design approach, Virginia Tech's team is composed of a variety of backgrounds, ranging from architecture and building construction to macromolecular science and civil engineering. As a team, we intend to positively impact the surrounding community with our design. Developing a community within our team is crucial to our success. Team members participated in various design charrettes, as well as individual research, which allowed our comprehensive design for the Eco-Park Learning Center to integrate all aspects of life and community.