TME (Transfer Multisort Elektronik Sp. z o.o.), a global distributor of electronic components with multimillion-dollar revenues, will showcase how Edge AI is enhancing automated vision-based quality control at this year’s electronica (Hall B5, Booth 361). The demonstration will feature the Arduino UNO Q, a compact platform that combines control and data processing capabilities to analyze images directly on the device. By processing visual data locally instead of transmitting it to external servers, the solution helps minimize latency, reduce network traffic, and enable quicker responses to detected defects or irregularities.
“Just a few years ago, automated vision control systems relied heavily on costly smart cameras and elaborate vision systems requiring significant financial outlays and specialised expertise,” says Paweł Sióda, Senior Product Manager, TME. “With compact platforms like the Arduino UNO Q, engineers can now rapidly build a demonstrator, test effectiveness through a pilot project and gradually expand their AI vision inspection capabilities in-house.”
AI vision inspection uses machine learning models trained on sample photos showing correct and defective elements. Once trained, the models can classify products, detect assembly errors, recognise colours and identify surface damages or illegible prints in real time. Rather than replacing human operators, these AI systems handle the monotonous inspection tasks with consistent accuracy, allowing operators to focus on verifying flagged items.
A typical architecture powered by the Arduino UNO Q integrates a compatible camera, LED lighting, a part presence sensor and a communication module to transmit classification results to operators or PLC, SCADA and MES systems. A power supply, cables and connectors complete the AI vision inspection station. The Arduino UNO Q natively supports Bluetooth and Wi-Fi, simplifying integration into factory networks. Engineers can initiate deployments with a low-risk proof-of-concept (PoC) on a single process before scaling across addition stations.
TME offers over 1.5 million products from about 1,500 leading manufacturers, providing all the required elements to builds a complete Arduino UNO Q demonstrator. Both 2GB and 4GB variants of the platform are available from TME.
Quality control using AI is just one example of the capabilities of the Arduino UNO Q platform. During electronica visitors are invited to meet the TME team (B5:361) to learn how the platform can also be also used for condition monitoring and vibration monitoring. Go to the page ‘Discover practical applications of Edge AI with Arduino UNO Q’ for more information.
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