Intel-Powered WaitTime Supports Low-Latency Edge Performance to Optimize Crowd Behavior
December 18, 2025
Blog
Crowd behavior and movements can be unpredictable. It’s important that areas that host large quantities of people, such as stadiums, concert venues, and convention centers, are capable of keeping individuals safe in real-time with high-performance analytics.
There are multiple factors to consider with the goal of navigating crowds and venues efficiently, like movement, density, and occupancy. AI technologies such as WaitTime supports these scenarios by delivering crowd-level diagnostics to strengthen operational efficiencies and ROI via data-driven insights into crowd behavior intelligence.
WaitTime uses imaging techniques to assess crowd movement and behavior, with the support of Intel hardware using Intel oneAPI Toolkit for heterogeneous workloads. Intel CPUs also provide low-latency edge performance via the 5th Gen Intel Xeon scalable processors, which further support the solution's ability to deliver on-site, real-time processing.
The Intel Geti software supports teams building computer vision models by easing the process of data upload, labeling, model training, retraining, and optimization tasks. For WaitTime, this software can support the building detection and tracking models for tasks like crowd and person detection.
WaitTime is a GDPR-compliant, camera-based solution capable of delivering high-volume precision for traffic counting (e.g., 900+ at sports gates, 5,000+ at conventions), versatility for complex scenarios, and real-time insights with operational dashboards and smart wayfinding algorithms.
Computer vision models on Intel hardware can help teams monitor the following:
- Entry/Exit: Tracks occupancy across a threshold;
- Queue: Organically forming crowds;
- Stanchion: Confined or governed lines, dots on the floor, stanchions, or other spatial restrictions;
- Massing: Percentage-based occupancy reading of the crowd.
The additional support from Intel’s VTune Profiler can help to locate and eliminate bottlenecks in computer vision models where real-time operation is critical for ensuring safety.
The WaitTime operator platform utilizes real-time and historical analytics to stakeholders aware, keep the crowds safe, and assist in making informed design decisions. The WaitTime guest platform utilizes displays and mobile integration to assist guests in making decisions, like short queues to optimize time and spending.
Intel’s Edge AI Initiative
This blog is part of a series outlining Intel’s AI Edge initiative. Intel recently unveiled its Intel® AI Edge Systems, Edge AI Suites, and Open Edge Platform. These are designed to help partners integrate AI into existing infrastructure and help them to jumpstart development and to increase trust in their system performance and security.
Intel is collaborating with its software partners to create and optimize AI for edge applications, as illustrated by this series of blog posts. Intel is working with its hardware platforms to specify Intel® AI Edge systems that allow for best-fit AI performance for key AI edge workloads and are available in a variety of power levels, sizes, and performance options.
To find out more, visit Intel Edge AI.
Tiera Oliver, Assistant Managing Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She develops content and constructs ECD podcasts, such as Embedded Insiders. Before working at ECD, Tiera graduated from Northern Arizona University, where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student-led newspaper, The Lumberjack.
