SIRAM OCR5 ALPR Deployed In Record Time Thanks to Deep Learning

When talking about the technological R&D sector, the adaptability and versatility of processes become a key value in all software development. The technological solutions must be scalable, offering maximum integration with other solutions and/or protocols, but also all solutions must offer maximum performance when operating on any support and device. This requirement is no different in parking, security and access control sectors. For this reason, from Innova Systems Group, as a development and implementation company of ALPR technological solutions, we ensure maximum versatility and fast technological deployment of all our products.

Our OCR5 automatic license plate recognition solution, like the rest of our SIRAM software products range, allows us to deploy our code on different hardware platforms in record time. This fast deployment can be done because OCR5 is an ALPR solution based on Deep Learning, as when deciding to develop OCR in this AI technology, very high-level programming languages had to be chosen, in which portability is one of its key characteristics. The efficient and fast response of OCR5 is possible due to the conjunction of Deep Learning + High-Level Programming Language that enables the option to migrate and scale our ALPR OCR5 solution in different operating systems and hardware platforms in less time than any other ALPR technology.

Currently, SIRAM OCR5 is available for x86-64, AMD64 or ARM platforms, as well as Windows or Linux operating systems. This allows us to offer All-in-One solutions where the OCR5 is running on the Axis camera (@TheEdge), which allows the user the option to choose a wide variety regarding the architecture type to implement, because OCR5 can run on Server Based and on All-in-One architectures, being able to combine both strategies in the same installation.

At Innova Systems Group we not only invest our best resources in creating OCR5 as a great ANPR technological solution, but we also guarantee scalability and implementation can be carried out almost automatically, minimizing code deployment times. Our technology OCR5 based on deep learning offers a quick implementation (code deploy) on different platforms.

Many studies analyze the differences between using high-level or interpreted programming languages versus low-level or compiled languages, being portability and speed of programming one of the main positive differences and characteristics of interpreted ones when talking about ALPR users´ experience. To be able to differentiate whether a solution is based on one or the other type of programming language, you only have to evaluate the ability of the solution to be deployed on different platforms or architectures simultaneously, as well as the manufacturer's response to any modification request, improvement or adaptation of the ALPR solution to a new scenario such as a new license plate type.

The implementation or deployment is an indispensable piece in the ALPR sector to offer global and specific requirements, attending to the needs of each application. When thinking of new technological solutions, this thought must be associated with software fast implementation and adaptability. From our side, OCR5 can be implemented on different devices and applications in record time, but also can give a response to different requirements or specific characteristics reducing code transition or translation times to the maximum.

About Innova Systems Group 

Innova's mission is to provide solutions for access control and for the management of traffic based on innovative technologies such as the recognition of license plates. It is renowned due to its customer service quality, facilitating the personal and professional growth of its employees, encouraging reconciliation measures, a good work environment, equal opportunities, and generating solid and sustainable benefits. All of this, searching the common good of society through a policy of corporate social responsibility which helps and generates opportunities for the most disadvantaged, and taking care of the environment.