Blight is a relative term. For some, they “know it when they see it.” However, newly embraced technology in Tuscaloosa, Ala., provides a more objective way to identify blight.

The University of Alabama and the city of Tuscaloosa collaborated to create a system that can automatically detect blighted areas in a community, helping prevent issues before they escalate into costly repairs for property owners. This patent-pending technology will reduce personnel time devoted to inspection, limit potentially harmful interaction on properties and uniformly expand detection to all parts of the city.

The inventors of the technology are Dr. Erik Johnson, assistant professor of economics in the Culverhouse College of Business, and Brendan Moore, executive director of urban development for the city of Tuscaloosa.

According to Moore, the two men first met in the spring of 2020, and a conversation sparked interest in this project.

“We discussed the idea of how we could identify potentially negative issues associated with properties or code violations, to identify those more quickly and easily,” he said.

Fast-forward to today, and the technology has been implemented with some successful outcomes that could be translated to future wins in other cities and towns.

“So, the way the technology works is that we, in Tuscaloosa, have really been able to leverage the fact that the city has a great municipal-owned waste management fleet here,” said Johnson. “So, we were able to put cameras on their garbage trucks, basically (with privacy and confidentiality in mind).”

Framing this conversation, Moore acknowledged blight is an issue in most communities but was more time and resource-intensive in theirs.

“You have to have the human capital and also the equipment,” he said. “So even when you start (surveying) tens of thousands of violations, and you only have a handful of either code enforcement officers or property maintenance inspectors, it makes it a little bit more intensive.”

The city frequently receives calls about overgrown grass, abandoned vehicles, litter, illegal parking and appliances or furniture left outside. The new technology can analyze images of properties and highlight issues using a scoring system.

That’s why this new solution has so much potential — it is objective. This system helps prevent neighborhood decline in an affordable way using a unique method to collect and analyze relevant data. The ability of the model to determine exactly what part of the property is driving the blight score can help inform property owners and lead to what Moore refers to as “low-cost interventions.”

That’s exactly why Johnson said its implementation can be a game changer. That’s because the more data deep-learning models are given to analyze, the more effective they become. He noted the city has been responsive in putting together data from across departments to inform the model. They’re also looking to share this scoring model with other municipalities.

But it’s still a work in progress, according to Moore.

“We’re still kind of in a testing phase,” he said. “And we’re implementing and kind of going by more of a block-by-block-type approach, which is mirroring what we’re doing in West Tuscaloosa. Obviously, while coming out of COVID, there’s a little bit more sensitivity, and (we’re) trying to be mindful of making sure we’re not putting any undue burdens on property owners who are already in a difficult situation. So that’s been a delicate balance.”

In hindsight, Moore said he’s proud of the project’s momentum and that they’ve expanded beyond what he refers to as “the why.” In his words, “it’s more of what we’ll call kind of a code violation or defect detector. So that could be anything from tall grass to junk cars, to blight, to pieces of property — really just anything that might be a defect in the built environment.”

And when issues are identified, or the homeowner or renter can’t afford the repairs, there are measures in place to address that. “Recently, our Community Development Office got (some funding) for these kinds of refreshes or repairs,” he said. “So, we’re optimistic that hopefully, we can connect some of those data points with that office as well to help and kind of inform their decision-making on the best places to spend less dollars.”