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Machine Vision / ALPR

Autonomous AI-based traffic surveillance system offers +98% accuracy

Adam FrostBy Adam FrostMarch 16, 20203 Mins Read
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A fully integrated artificial intelligence-based (AI) autonomous traffic surveillance and anomaly detection system has achieved near-100% accuracy test results for a Smart City deployment in Texas.

Machine learning and computer vision systems developer Currux Vision Corp has released test results for its Smart City AI traffic video analytics and management solution trialled by the City of Grapevine, and independently by camera and video surveillance systems manufacturer Costar Technologies. Corrux’s AI-based autonomous traffic monitoring platform offers accurate real-time traffic analytics and alerts to accelerate response to incidents, optimise transportation infrastructure, and reduce congestion and pollution. While most traffic management systems are time consuming, inefficient, and costly, Corrux and Costar are creating a new AI-based system that they hope will take traffic analytics and management to the next level by enabling cities, governments and Departments of Transportation (DOTs) to autonomously monitor traffic cameras.

The Currux Vision Smart City AI solution removes the need for constant human oversight, outdated reporting systems, and limits on observation time by autonomously monitoring traffic cameras and systems and generating real-time alerts when certain events of interest occur. The company offers one of the most advanced, reliable, and cost-effective AI traffic detection systems, with attributes that include counting and identifying vehicle types, slow traffic, wrong-way traffic, speeding, parking infringements, pedestrian detection and counting, and other features. The dashboard provides extensive analytics and reports and does not require a separate video management system to operate.

The test with the City of Grapevine, and independent testing by Costar Technologies confirmed that Currux’s Smart City AI system can operate with 95-98% or higher accuracy under various conditions including day and night, rain, camera vibrations, and even partial camera view obstruction. Additionally, the ease of installation and operation, edge and near-edge processing capabilities, powerful and flexible back-end capabilities, and attractive price point have been cited as key differentiators for the product. The two Texas-based companies note that Costar’s Cohu-brand high resolution, imaging cameras and systems are an ideal platform for deploying Currux’s AI and computer vision solutions in transportation, as well as security, military, enterprise, residential, and industrial sectors.

“The urbanisation, increased traffic, and climate change drive the urgent need for a next-generation traffic monitoring and management solution like our Smart City AI product,” explained Alex Colosivschi, founder and CEO of Currux Vision. “Today, the deployment of traffic cameras in cities is hampered by either lack of or subpar autonomous video monitoring systems that require cloud access or extensive high-bandwidth internet infrastructure. We designed the Smart City AI product to significantly accelerate wide-scale adoption of AI-capabilities by cities and businesses both in the USA and internationally. We are happy to have a great partner like Costar to accelerate this transition.”

Mathiew Bais, CTO of Costar Technologies, commented, “For the past two years we have tested numerous video analytics solutions that our municipal, DOT, and private customers require with various degrees of success and accuracy. The Currux Vision AI system brings the accuracy, flexibility, ease of installation and use, and the price point that we believe is required for wide acceptance by cities and DOTs.”

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Adam Frost

Adam joined the company in 1994, and has been News Editor of TTT since 2009. In his other role as Circulation Manager, he helped create the original Traffic Technology International distribution list 23 years ago, and has been working on it ever since. Outside of work, he is a keen fisherman, runs a drumming band, and plays an ancient version of cricket.

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