The University of Alabama’s Bryant-Denny Stadium holds over 100,000 fans. On September 19, 2026 vs Florida State, fans were getting to their seats faster with the help of new data from WaitTime software. WaitTime, powered by Intel® Xeon® processors, measures lines and how fast they’re moving to inform stadium operators. The technology has led Alabama to change how seating gates are numbered, staffing placement and point-of-sale adjustments to smooth the flow and give fans a better experience. (Credit: Intel Corp.)
On college football Saturdays, more than 100,000 fans fill the University of Alabama’s Bryant-Denny Stadium in Tuscaloosa. The energy is electric, and fans don’t want to miss a minute of the action kept waiting in long entrance lines or at concession stands. Those issues had been the top complaint in Alabama’s postgame surveys.
Now, fans are noticing some big changes. "I think it’s fantastic, look at the line right here. I was able to get in and out and grab my food and drinks very quickly," said one fan at a recent 2026 Alabama v. Florida State game. Another added, "You want to get your water, it’s so hot. If there’s no line, boom, I’m there."
That smoother fan experience comes from real-time crowd analytics powered by edge AI. By processing AI at the edge using Intel® Xeon® processors, the University of Alabama can spot congestion and respond immediately.
Crowd Management AI for Shorter Stadium Entrance Lines
With a capacity of 100,077, Bryant-Denny Stadium is the nation’s seventh largest. To reduce delays, the university partnered with WaitTime, a provider of real-time crowd intelligence software.
WaitTime uses strategically mounted overhead cameras that measure pixels - able to detect the difference between a human and a trash can - and watch how those pixels move. It’s 100% anonymous. The software is already being used in more than 25 sports, convention and shopping venues worldwide, and the University of Alabama deployment extends its use further into college football, joining The Ohio State University.
An Axis Communications sensor sits above a concession stand at Bryant-Denny stadium in Tuscaloosa, Ala. It measures collections of pixels to determine humans and what direction they are moving in and how long they stay in one designated queue area. Alabama Athletics uses a growing network of 120 of these sensors to measure crowd flow across its football stadium and basketball arena. (Credit: Intel Corp.)
Rand Harris, Alabama’s chief technology officer and associate athletic director, first saw the technology in practice at Levi’s Stadium in Santa Clara, California, during the 2019 National College Football Championship.
“The first thing I noticed was that the lines were shorter than what I'm accustomed to on a typical game day here. Right after that was signage, arrows and times and red, yellow and green lights that just made sense visually of like, wait a minute, what are they doing here?” Harris said. “We then deployed the WaitTime system last summer (2025) and within the first two games immediately started seeing we have some operational issues we would love to fix.”
Benefits of Processing AI at the Edge
Alabama’s network includes more than 100 sensors across concession stands and entrance gates in the football stadium, plus 20 more recently added sensors in the basketball arena. For real-time analytics, the university processes the visual data locally on six Dell servers powered by 12 Intel Xeon processors.
Processing AI at the edge like this delivers three key benefits for a venue: lower latency, faster operational decisions and greater data privacy. Instead of sending raw video to a data center via the cloud, the system analyzes it at the stadium.
"There's no time budget for a round trip to a distant data center and back. Processing locally at the edge means the decision to open a gate or add staff happens in the same moment as the problem. Processing at the edge means the raw video never has to leave the stadium," said Renu Navale, vice president of the Edge Computing Group at Intel.
A live WaitTime dashboard image during the September 19, 2026, football game vs. Florida State captures the crowd of fans at one entrance just before kickoff. On the left side of the image, the red, yellow and green indicators represent the lines at other gates and concessions stands that stadium operators monitor. (Credit: Intel Corp.)
Intel Xeon Processors for Real-Time Data Analytics
Using Intel Xeon processors allowed the university to run WaitTime’s AI workload on its existing computing infrastructure. According to the university, that approach provided the required performance while aligning with its current environment and avoiding the cost and complexity of specialized hardware.
WaitTime optimizes its software for a CPU-only architecture, enabling the system to distinguish between people moving through a space, gathering nearby or progressing through a line—all in real time.
"With WaitTime’s artificial intelligence we’re able to distinguish, are you actually in line progressing toward the front? Are you congregated off to the side or just passing through? We can determine the difference between all those behaviors,” said Zack Klima, CEO and founder of WaitTime. “Intel has allowed us to leverage our CPU-only architecture to achieve those real-time results."
Real-Time Crowd Data for Improved Operations and Revenue
The real-time insights produced immediate operational improvements. After deploying the system, stadium staff identified bottlenecks at entrance gates and adjusted where security checks and ticket scanning took place.
"We’ve changed where the security perimeter starts so we can do checks versus where the scanning of the ticket takes place. Not only is it a fan improvement of speed, but we’re also seeing more revenue at the end of the day just by being more efficient at these lines," Harris said. "The faster we can get them in and seated, the more they experience the game, the more concessions, more merchandise, everything that benefits us too at that point."
CAPTION: A screenshot of the Alabama Athletics fan app shows the red, yellow and green indicators representing the wait times at concession stands on the stadium’s upper level. Fans can see these live wait times at security entrances, seating gates and concessions in real time to make the best decision so they don’t miss any of the game. (Credit: Intel Corp.)
The university also shares real-time crowd data with fans through its athletics mobile app. Red, yellow and green indicators help fans identify the fastest nearby entrance gates and concession stands.
"It is faster, more efficient," Harris said. "The fans feel more empowered to handle it themselves anyway and seem to love that approach."
The results are reflected in fan feedback. Long waits at entrance gates—once the stadium’s No. 1 complaint—no longer rank among the top 10 issues in postgame surveys.
Historical crowd data is also guiding longer-term investments. For the 2026 season, the university converted 19 concession stands into AI-powered grab-and-go kiosks after the data revealed recurring delays. The checkout-free kiosks can process transactions up to four times faster than traditional cashier lines, helping fans return to the game sooner while increasing revenue opportunities.
For sports and entertainment venues, the benefits of edge AI are practical and immediate: faster insights, quicker responses to crowding, greater control over data and a better fan experience. At Alabama, processing AI at the edge on Intel Xeon processors is helping turn real-time analytics into shorter lines, smarter stadium operations and new revenue opportunities.