Mairano, Italy and Tel Aviv, Israel – September 14, 2022
Italian Automatic Number Plate Recognition (ANPR) specialist, Tattile, part of THK Group, announced today its technology partnership with leading edge AI chipmaker Hailo to power their next generation of high-end cameras: the “SMART+.” The Hailo-8™ AI processor will be integrated into Tattile’s new product line, enabling a new era of smart cameras for Intelligent Transport Systems (ITS), mobility and smart cities.
The License Plate Cameras (LPC) market is expected to reach over $700 million by 2028. LPR cameras remain one of the most popular video analytics applications for smart cities as they can be easily deployed on highways, toll booths, and parking lots to enable fast vehicle identification, congestion control, automatic fare collection and more. By integrating a powerful edge AI processer, such cameras will reach new levels of effectiveness and efficiency, running ALPR in real time. This is crucial for reducing product miss-rates, decreasing detection latency, lowering overall costs, and increasing data protection.
“Hailo’s AI expertise, extensive collaboration from design to integration and top-notch solutions made them the perfect partner to help power our next-gen LPR camera line,” said Corrado Franchi, CEO at Tattile. “Hailo-8 offers market-leading performance both in terms of tera-operations per second (TOPs) and frames per second (FPS) per watt with exceptionally low power consumption. The demand for sophisticated ANPR solutions is rising, and, with the help of this integration, we are perfectly situated to drive forward a new era of mobility.”
The new Tattile camera line represents the next generation of highly scalable smart cameras. Tattile’s ITS systems go beyond pure ANPR, offering a true vehicle identification system with functions as well as levels of integration which cannot be found elsewhere on the market. The integration of the Hailo-8 will offer Tattile’s high-end Smart+ camera line enhanced performance while shortening time to market.
“We are honored to be selected by such a significant player in the ITS space as Tattile and their world-class engineers as a technology partner,” said Orr Dannon, CEO, and Co-Founder of Hailo. “This collaboration will result in better-performing cameras for a wide range of mobility use cases. We look forward to further bolstering the technologies powering the smart cities of the future.”
Hailo and Tattile will be presenting at the ITS World Congress in LA on September 19-22, 2022. To pre-schedule a meeting with Hailo, please use this link.
Since 1988 Tattile has developed and produced License Plate Reader (ANPR/ALPR) cameras and application software for ITS, Mobility & Smart Cities; today Tattile is a world leader in intelligent traffic monitoring systems. We are fully engaged in creating of high-tech, cutting-edge ANPR (ALPR) and vehicles identifications applications mainly based on AI (Artificial Intelligence). These systems fulfill the most demanding applications in the ITS and Big Data Analysis markets. The average team age is 36years; an impressive 40% of the team works in R&D, making Innovation, Customer Orientation, and Flexibility the core company values. All Tattile smart traffic cameras, free-flow tolling, and speed enforcement systems comply with strict quality standards, ensuring reliability and cost-efficiency. For more information visit www.tattile.com
Hailo, an AI-focused, Israel-based chipmaker, has developed a specialized AI processor that delivers the performance of a data center-class computer to edge devices. Hailo’s processor is the product of a rethinking of traditional computer architecture, enabling smart devices to perform sophisticated deep learning tasks such as object detection and segmentation in real-time, with minimal power consumption, size, and cost. The processor is designed to fit into a multitude of smart machines and devices, impacting a variety of sectors including automotive, Industry 4.0, smart cities, smart homes, and retail. For more information visit https://hailo.ai/