Research News

UB-linked startup develops technology that streamlines process of detecting fevers

An example of a thermal image of several people.

A new technology that uses thermal imaging similar to what is pictured here may help streamline the process of detecting fevers in offices and public spaces.


Published September 3, 2020

headshot of Thiru Vikram.
“The ultimate goal of the pilot project is to prove that Bifrost is a better option than using a handheld IR measuring device by comparing rates of false positives and negatives. ”
Thiru Vikram, CEO
Buffalo Automation

Buffalo Automation, a startup company with UB roots, is setting a new course that could eventually help organizations around the world better navigate return-to-work plans amid the COVID-19 pandemic.

The primary focus of the company, which was founded in 2015 by CEO Thiru Vikram and two fellow UB engineering undergraduates, has been to develop and implement AutoMate, an artificial intelligence (AI) system that enables ships and boats to essentially drive themselves. It uses thermal imaging to detect and steer around other vessels, buoys, swimmers, the shoreline and other non-water bodies during periods of poor visibility.

Now, in the wake of the coronavirus crisis, Buffalo Automation is piloting a new project that is adapting its technology to streamline the process of taking body temperatures in the workplace.

The company is running a pilot program, which is called the Bifrost project, at a facility operated by UB Neurosurgery, a member of the UBMD physicians’ group, the practice plan of the Jacobs School of Medicine and Biomedical Sciences at UB.  

Bifrost equipment — which uses thermal imaging to measure people’s temperatures — was installed on July 1 at the UBNS Comprehensive Neuroscience Center, located on George Karl Boulevard in Williamsville. The equipment scans people as they walk past a revolving door from an indoor balcony. Smaller, battery-powered units will be installed in two check-in kiosks within the next month.

This thermal image was generated by Bifrost, a new technology that can detect the body temperatures of several people at once. Image: Buffalo Automotion

Currently, the equipment is gathering data, validating the ability to do long-range facial detection and feature extraction using thermal images. In the next phase of the project at UBNS, it will begin to compare and validate temperature differences between facial features using an instrument called a microbolometer, which detects infrared radiation.

“As we see many patients in the community, Buffalo Automation reached out to explore synergies that may exist,” says Elad I. Levy, SUNY Distinguished Professor, L. Nelson Hopkins Chair of Neurological Surgery, professor and chair of the Department of Neurosurgery in the Jacobs School. “I think as researchers at UB, we all share a common interest in using science to augment health in our community and globally.”

This is the Bifrost equipment as currently set up at the offices of UBNS, the neurosurgery practice of UBMD Physicians' Group.

According to Vikram, Bifrost got its start early in the pandemic, when shipping companies that the startup had contracted with were reluctant to proceed because they feared Buffalo Automation staff would inadvertently infect ships’ crews, in spite of the “extreme precautions” the Buffalo team was taking.

“One of us then flippantly suggested in the office that AutoMate should be able to tell if our engineers had a fever before embarking on a vessel ... and Bifrost was born,” Vikram explains.  

“Bifrost does not need super-expensive and periodically calibrated thermal cameras to work,” he notes. “It is essentially a simple Software as a Service (SaaS) solution that makes an existing thermal-camera solution work just right and, most importantly, is a viable solution for scanning large crowds from a distance.”

Vikram describes Bifrost as a Convolutional Neural Network (CNN) that identifies and extracts the inner canthus (IC) — the inner corner of the eye — from each human face contained in a given thermal image. It then extracts other facial features, such as foreheads, noses, ears and necks, from each human present in an image. After comparing patterns in the metrics in various individuals, it isolates individuals with abnormal temperatures.

In other words, Bifrost takes specific human features from thermal images and measures the skin temperatures from areas most likely to indicate a fever.

“The ultimate goal of the pilot project is to prove that Bifrost is a better option than using a handheld IR measuring device by comparing rates of false positives and negatives,” Vikram says.

If a fever is detected, there will be a secondary screening using traditional methods for any individuals flagged by Bifrost, he adds.

The anonymized information will not be shared with any outside entities, Vikram says. However, images will be sent to Buffalo Automation for training purposes.

By taking the temperatures of multiple people simultaneously, Bifrost hopes to eventually streamline a tedious and expensive process that requires trained personnel and often results in people having to wait in line — thus saving time and money.

While some may think the technology could present privacy issues, Vikram maintains it is conceptually similar to closed-circuit TV cameras being used in public areas for security reasons. In fact, he says, “Bifrost offers more privacy, since it is very difficult to recognize someone’s face in a thermal image.”