The Rekor system will be demonstrated at the ITS World Congress 2022.

Rekor, (NASDAQ: REKR) which uses AI, machine learning and data to support roadway safety and smart mobility, unveiled its new edge-based, non-intrusive, AI-driven traffic data collection system designed and developed to collect and transform high-speed roadway data. (Rekor.ai)

The high tech system uses computer vision and proprietary “edge-based” optical sensors, which provide AI processing directly on the device for secure, high quality, holistic traffic insights in real-time. It collects federally mandated vehicle classification data that is also displayed on a cloud-based analytics dashboard for faster and more accurate decision making for transportation planning, roadway engineering, and traffic management.

The system is a massive improvement over the hitherto physical process that entailed closing driving lanes for deployment of measuring equipment, or digging up roadways to install sensors. The process was inefficient, unsafe and suffered from recurring maintenance issues.

In contrast, Rekor’s “non-intrusive” systems provide high-quality, high-resolution data analytics accurately classify vehicles using the 13 vehicle classifications established by the Federal Highway Administration (“FHWA”), as well as information such as vehicle speed, vehicle volumes, traffic patterns, and a range of other data including vehicle type and tonnage, instances of electric vehicles traveling on roadways, and estimates of greenhouse gas emissions emanating from identifiable instances of traffic and congestion.

“Now state agencies, Metropolitan Planning Organizations, and commercial developers can safely deploy advanced AI sensors in minutes, not days, and at less dangerous locations off the roadway, eliminating the need for “on the roadway construction,” said David Desharnais, President, Rekor. “This system is scalable, affordable and will help departments access federal funding, improve mobility, and better the lives of their citizens.”

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