CTC is working on innovative software that will make machine vision systems more accessible to company staff

The CTC Technology Centre is currently developing a software tool that will make machine vision systems implemented in companies simpler and more accessible so staff can update and obtain information from the system autonomously and smoothly.

Machine vision systems can be complex to use and update for non-innovation-savvy staff in companies. Depending on the objectives to be achieved with this technology, the algorithms that make up the system must be adapted to the final problem, besides carrying out the tasks of data pre-processing, post-processing of the results, communication and management of the information collected, among others. This lack of accessibility prevents many companies from taking full advantage of the solutions in place.

CTC seeks to solve this problem by developing a software tool that will facilitate the execution of all the processes associated with artificial vision systems.

This tool is based on a simple and intuitive interface designed to allow non-innovation experts to perform the tasks in this type of system, such as data pre-processing, data flow management, image labelling, model training or the generation of reports and alarms.

The project will integrate a machine vision camera, processing equipment and the interface into the production line, so the operator can run and manage all the collected data in real-time from his workstation. In this sense, besides optimising accessibility, this tool will help increase processing speed and reduce latency.

The innovative tool will also bring data processing and storage closer to the production line. This is known as Edge Computing, a technology that aims to process data on users’ own devices, avoiding sending it to “the cloud” and bringing the ability to manage this information from the company’s own databases.

The project is funded by the Regional Ministry of Universities, Equality, Culture and Sport through the call to promote knowledge transfer.