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.


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.

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.

The Mycorrho-grid is a blockchain based microgrid inspired by the way trees collect and distribute resources through mycorrhizal networks in the forest. It was first developed in conjunction with Virginia Tech’s grand-prize winning TreeHAUS entry in the 2019 Solar Decathlon Design Challenge and is expanded upon here with a focus on further potential for biologically inspired functionality. The baseline case as simulated in the competition is a 12-unit multi-family microgrid with a shared 50kW rooftop solar array and fixed price return from the grid.

There has been a trend in applying imaging techniques in building facade inspection, such as laser scanning, infrared thermography, high definition camera, etc. Utilizing such techniques creates a large amount of multi-sourced image data for building facade inspections. However, there is a lack of an effective way to manage these massive image data in aspects of spectral, spatial, and temporal data. As GIS is specialized in the storage and analysis of spatial and raster data, it can provide a good working platform for archiving and processing massive image data.

The role of building science education examined in the context of past DOE student competitions.

A presentation part of panel discussion at the 5th RBDCC. This paper presents findings from a meta analysis of DOE Student Competition Guidelines and competition winners in terms of Building Science keywords and requirements. 


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.

The TreeHaus is a design for a net-positive, regenerative housing development inspired by the way trees collect and distribute resources in the forest. The goal of the project is to create a building that strengthens its surrounding environment and municipality by imagining it as a constituent of its contextual ecology. The TreeHaus will harness energy from the sun, harvest water from the rain, and cycle resources and information throughout its community in the same way that plants and trees do through networks in nature.

Over the past years, a growing trend of utilizing camera-equipped drones for periodical building facade inspection has emerged. Building façade anomalies, such as cracks and erosion, can be detected through analyzing drone-captured video, photographs, and infrared images. Such anomalies are known to have an impact on various building performance aspects, e.g., thermal, energy, moisture control issues. Current research efforts mainly focus on computational image processing methods to recognize certain types of facade anomalies.

With the growing concern of climate change and more frequent and severe natural disaster events affecting the built environment, enhancing the performance and resilience of buildings has become increasingly vital. Stakeholders are seeking guidance towards improving both the individual performance of buildings and systems as well as their overall disaster resilience. Thus, they require tools that can comparatively evaluate technologies across multiple standards and qualities of construction in a consistent way.