Seoul Robotics Introduces Critical Asset Monitoring Solution In Partnership with Herzog
Joint application integrates Seoul Robotics’ 3D perception software with Herzog’s occupancy detection suite to ensure greater safety for rail passengers, operators, and pedestrians
Seoul Robotics, the 3D computer vision company using deep learning Artificial Intelligence (AI) to power the future of mobility, and Herzog Technologies Inc. (Herzog), a leading railroad systems and technology integrator, today jointly announced the introduction of an automated obstacle detection and warning system aimed at making the interface between the railroad and the public safer. Critical Asset Monitoring (CAM) combines Seoul Robotics’ 3D perception software, SENSR-I™, with Herzog’s occupancy detection platform with the goal of reducing future railroad incidents.
CAM is an integrated solution that utilizes a multi-sensor hardware platform and 3D perception engine to track and classify objects. This edge detection is coupled with business intelligence, which allows the system to analyze the information in real-time and make timely decisions for notifying the appropriate entities. CAM can detect humans, vehicles, bicycles, and other foreign objects, enabling it to provide unparalleled safety insights. A powerful component of the system is the ability to evaluate the situation according to complex conditions as well as the behavior of the objects being monitored. This enables the system to make smart decisions that are specific and unique to each area being monitored.
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“We pride ourselves on equipping our partners with solutions that will improve safety and efficiency. CAM provides customers with the ability to monitor aspects of their critical infrastructure in ways previously unavailable. With this innovative technology, our goal of improving safety is now within reach,” said Glen Dargy, Vice President of Technology at Herzog. “By integrating our products and services with Seoul Robotics’ software platform, we are providing an industry-leading solution.”
Since 2011, over 23,000 incidents have occurred where trains have struck trains or people, resulting in 2,700 fatalities and 9,500 injuries, according to the U.S. Department of Transportation Federal Railroad Administration. By using CAM systems at crossings, bridges, tunnels, stations, and other areas of critical interest along the corridor, train conductors and operations personnel are programmatically alerted to hazards detected in monitored areas. The solution is being implemented by Trinity Railway Express, a commuter rail operator between Fort Worth and Dallas, Texas, with engineering underway for several additional bridges, crossings and passenger stations with other operators.
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“For a rail detection system, every second is critical. Trains need adequate time to fully stop and require advanced warning to reduce the chance of a collision. This is only possible with an accurate, highly granular 3D perception system like ours,” said Jerone Floor, Vice President of Product at Seoul Robotics. “Through our partnership with Herzog, we are making this technology available to any rail operator, ensuring they can cost-effectively access these insights and make every second count.”
Seoul Robotics’ proprietary software, SENSR-I, uses deep learning to analyze and understand 3D sensor data with unrivaled accuracy. SENSR-I enables the detection of more than 500 objects up to 200 meters ahead, predicts motion up to three seconds in advance, and provides real-time object perception. SENSR-I is compatible with more than 75 different types and models of 3D sensors and even supports systems consisting of different brands of sensors, making the technology cost-effective and scalable over large geographies. SENSR-I also comes equipped with dynamic weather-filtering AI that enables CAM to glean and decipher obstacles even through harsh weather conditions, such as snow or heavy rain.
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