From complexity to simplicity

Innovative and adaptive all-in-one ANPR technology solutions deliver high reliability and accuracy with a quick return on investment

Words | Zsofia Karetka, Adaptive Recognition

Vehicle detection rate is one performance indicator with profound financial implications for traffic Above: Vidar ANPR camera for traffic monitoring with built-in laser trigger. L-R; Single-optic monitoring system operators. camera with cloudConsider what a 0.1% difference based ANPR; Dualmeans in the case of an ETC optics camera with (electronic toll collection) system with, say, 6 million events per day, which counts as medium-size. onboard ANPR; Dual-otics camera with onboard ANPR & radar; Single-Missing 0.1% represents 6,000 optic camera with vehicles a day. Assuming that cloud-based ANPR 2% of these vehicles are unauthorized & radar users - again, a real-life average - and calculating with a US$50 fine for each, we are talking about missing out on more than US$2 million of income per year. In the case of a pay-per-use tolling system, each and every missed vehicle represents missed income, which, calculating with the same numbers as above, amounts to US$100 million.

It is easy to see why maximising the vehicle detection rate is in the operator's interest. There are several ways to achieve this, but the methods and technologies widely used in the industry are either costly, high-maintenance, or both. To get something close to 99%, you need a laser scanner, radar, and induction loops. The latter requires breaking asphalt, which implies costly downtime. Induction loops also wear down quickly. Depending on several factors such as road quality and traffic, manufacturers recommend replacing them every five years or so. Adaptive Recognition's answer to this challenge is Vidar, a traffic monitoring ANPR camera with built-in triggers (laser and software-based) that delivers results without the high cost and maintenance. "The market is very price-sensitive, and maintenance can be a major cost factor,” says Márton Sipos, product director for Vidar. “What operators want is a simple, easy-to-maintain

system. That is what we provide, for about a third of the price of a complex system involving many components and different vendors for each. They get plate recognition, make and model recognition (MMR), and laser triggering in one single device instead of at least three. They save huge amounts on installation and maintenance without having to compromise on quality. Closing off one lane for a couple of hours costs hundreds of dollars, and it also impacts the economy in ways that are hard to quantify. Our cameras selfdiagnose, and maintenance can be performed on them remotely." Based on the above numbers, the investment in an all-in-one device like Vidar can return in 36,000 The number of plate types a single day. And from an aesthetic point of view, they are also incomparable to monitoring systems consisting of multiple from around the globe different components. recognised by the Carmen software engine

Evolving with the times

All Adaptive Recognition ANPR cameras are powered by Carmen, the company's plate recognition software developed in-house. Carmen is available on-board the cameras,

separately as a software development kit or as a cloud-based subscription.

The secret of Carmen's success is continuous development driven by client feedback. Engine updates come out every quarter to include new table types and formats as soon as they appear, as well as enhancements based on integrator requirements around the globe. The emphasis on responsiveness to client needs results in a win-win situation. Integrators get what they need quickly, and the product now boasts unparalleled worldwide coverage: 36,000 plate types from all around the world are recognised by the engine, and it keeps getting more robust with every update. Results are available in less than 100 milliseconds.

From a purely business point of view, reliable accuracy is important for system operators as it reduces the need for manual checking performed by humans, another costly item on their bill. Carmen provides this even in highspeed, multilane traffic situations.

Anyone with experience in traffic monitoring knows that poor visibility conditions and damaged plates are the enemies of accurate plate recognition. Carmen answers this challenge by leveraging AI to provide an informed guess complete with a confidence rate. In any case, the algorithm has been specifically trained to handle suboptimal images and does so with outstanding results.

Some highway operators use the software purposely for back-office checking. Carmen is currently used in more than 100,000 installations in various traffic monitoring systems around the world.

Above: Carmen ANPR software by Adaptive Recognition

All of Adaptive Recognition’s products, software or hardware, are developed and manufactured in-house. Integrators can design a system that delivers maximum results with fewer parts while saving time and money on installation and maintenance. Instead of managing multiple vendors for different system components, they have one single point of contact, and their custom requests are readily accommodated. ■

Decades of expertise

If you are familiar with the automatic number plate recognition (ANPR) industry, there is a good chance you have come across ARH, Adaptive Recognition’s former brand. ARH is well established in this field. Behind the new Adaptive Recognition brand, the people, the experience, and know-how remain.

“We are technology vendors who have been around for more than three decades, closely following the evolution of the sector and the market,” says Adaptive Recognition CEO, László Kis. “Our client base consists of traffic monitoring system integrators and operators. We know what kind of challenges they face in their daily work. They choose us because we understand their business and motivation. We think of our technology as a means to achieve goals. Above all, the principal goal is road safety, but we also consider our partners’ pragmatic business goals, such as time- and cost-effectiveness. How far can we simplify integration without compromising quality? How can our technology enable our clients to execute their business plans and ensure operational stability? These are the kind of questions that we ask ourselves when we develop our products, be it software or hardware.”