ITS Georgia Annual Meeting 2024

Rekor Attends ITS Georgia Annual Meeting 2024, Speaks on Augmenting Vehicle Classification with Image-Based Deep Categorization

Rekor attended the ITS Georgia Annual Meeting from September 15-17, 2024 in North Augusta, SC. Rekor participated in this in-person event by exhibiting its best solutions for urban mobility and transportation management at booth 6, and through presenting on using AI to enhance vehicle classification on September 16.

Rekor attendees included Terry Robinson, Justin Smith, Ben Gohlke, Rankin Reinholt, Eric Boivin, Mark Boivin, and Jason Holloway, who engaged with industry professionals throughout the event.

Rekor Highlights:

Rekor exhibited at booth 6 and presented its leading solutions for ITS Georgia attendees, Rekor Command™ and Rekor Discover™. The Rekor team discussed Rekor Traffic Services as well, which offers traffic data collection services using both traditional and AI-based approaches.

• ‍Rekor Command™: Through the use of our proprietary AI algorithms and technology, the Rekor Command™ platform detects events by transforming raw roadway and mobility data into actionable insights, ensuring transportation teams can respond to events disrupting the roadways in a timely and efficient manner, while also enabling the insights needed to analyze past performance and make collaborative data-driven decisions to drive improved performance of the roadways in the future.‍
• Rekor Discover™: Rekor Discover™ is a cutting-edge platform that addresses the limitations of traditional traffic data collection methods, which are often unsafe, costly, and inefficient. By leveraging AI-powered roadside systems, Rekor Discover™ automates the capture of comprehensive traffic and vehicle data, offering transportation organizations robust analytics and actionable insights.

Speaker Session: "Augmenting Vehicle Classification with Image-Based Deep Categorization"

On September 16th, Ben Gohlke presented, detailing how the Federal Highway Administration’s current vehicle classification framework (along with existing commercial technologies) doesn’t take advantage of all information available. By integrating advanced AI models and using its data, we can unlock more profound insights and gain even more value from traffic studies, such as Image Contextual Understanding and Advanced Categorization.  

Highlights:

• Transportation departments across the United States have been actively engaged in a variety of monitoring and measurement initiatives aimed at understanding traffic patterns. These studies revolve around metrics such as vehicle counts, speed, and classification.
• Vehicle classification has relied on the Federal Highway Administration's recommendations, encompassing both the traditional six and more recent thirteen bin characterizations. These predetermined bins serve as essential tools for traffic studies and the design of highways and roadways.
• However, the use of predetermined categorization, while invaluable, also leaves a wealth of untapped information about vehicles. Recent advancements in machine vision and AI-based processing present an exciting opportunity to extract significantly more data and value from these vehicle observations, nearly in real-time.‍
• Rekor presented methodology, technology, and proof of concept results from recent extensive deep classification research that leveraged edge-based machine learning algorithms with extensive foundational models to extract detailed information about vehicles, going beyond the fundamental FHWA bin classification. 

Rekor was delighted to join the ITS Georgia Annual Meeting 2024. It was a pleasure to speak with transportation professionals at the booth about Rekor Command™, Rekor Discover™, and Rekor Traffic Services. A special thanks to Ben Gohlke for positioning Rekor as an industry leader in his masterclass on AI’s impact on traffic studies.