Evolution Robotics Announces LaneHawk™ Loss Prevention Solution to Combat Retail

„LaneHawk Helps Retailers Turn Bottom-of-Basket Losses into Profits Using Proven Object Recognition Technology
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\r\nPasadena, CA – July 21, 2004 – Evolution Robotics, a leading provider of next-generation robotics technologies and component solutions, today announced the availability of LaneHawk, a solution for retailers that prevents loss and increases profits by automatically ringing up under-cart items. Using Evolution Robotics’ advanced object recognition technology, LaneHawk provides retailers with an effective solution for limiting inventory shrinkage due to retail fraud.
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\r\n“;““We believe that LaneHawk will have a tremendous impact in reducing retail fraud,” said Alec Hudnut, President of Evolution Robotics. “Retailers implementing this solution can be confident that items passing through their check-out lanes will be accounted for, which translates to positive bottom line results. For example, if a retailer loses $10 per lane each day from unpaid items in a 50–store chain, the annual loss in revenues amounts to about $2 million. LaneHawk recovers that revenue.”
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\r\nIn big-box and grocery retail outlets where customers rely on shopping carts, cashiers can easily miss items on the bottom of the cart in the check-out process. Check-out lanes at these retailers are often hectic for both the cashier and the customer, and even large items are routinely overlooked as a result. In addition to preventing this loss, LaneHawk also improves check-out lane productivity by no longer requiring cashiers or customers to lift items out of the bottom of the basket.
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\r\nLaneHawk is trained to recognize and identify each product likely to be placed under the shopping cart. A smart camera is flush-mounted in the check-out lane utilizing Evolution Robotics’ patented object recognition technology to match items under the cart to each store’s list. This recognition technology is extremely accurate; distinguishing unique features from each product to ensure nothing is overlooked, including multiple or partially-blocked items. The system only looks for items it has been trained to recognize, therefore the error rate is very low. LaneHawk is compatible with any point-of-sale system.
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\r\n“In my thirty-five years in supermarket security, I’ve seen retailers try a variety of methods such as mirrors and closed circuit cameras to mitigate the losses of missed items at the bottom of their shopping carts, with minimal success,” said Chuck Miller, an independent retail security consultant and former Vice President of Loss Prevention Services for the Food Marketing Institute. “According to a 2002 National Retail Security Survey report on retail theft, inventory shrinkage cost U.S. retailers over $31 billion annually. LaneHawk’s ability to recognize objects left under the cart is a valuable solution because the cashier never has to remember to inspect the cart. Retailers using LaneHawk will quickly see their shrink decrease and revenues increase.”
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\r\nThe product is now available to retailers worldwide. For more information please visit www.evolution.com.
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\r\nAbout Evolution Robotics
\r\nEvolution Robotics™ provides state-of-the-art robotics software, component technologies, and professional services that enable companies to develop intelligent devices and robotic products. The Evolution Robotics Software Platform (ERSP™) includes a state-of-the-art robotics software architecture, application development tools, and core robotic functionality modules in the areas of computer vision, autonomous navigation, and human-robot interaction. These technologies are designed to be ported to various platforms and processors to support clients’ needs. Evolution Robotics mission is to accelerate the robotics and intelligent device industries and help spur the creation of a variety of highly-functional products that will become indispensable in our daily lives. Evolution Robotics is an operating company of Idealab, a creator and operator of technology businesses. www.evolution.com\r\n
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