 Tools and devices are becoming increasingly intelligent thanks to artificial intelligence algorithms. They can now provide advanced features customized for each user, allowing better services and a more personalized user experience. But the fact that user identification technology often involves sharing data in the cloud raises issues of confidentiality. This is even more of a concern with images when they are used for face recognition. Thanks to the powerful STM32 capabilities, ST Microadronics has developed a solution to embed and run face recognition locally on a single-cost effective microcontroller. This is a solution addressing privacy concerns by processing images locally without using the cloud. Implementing face recognition on STM32 MCUs reduces considerably the bomb cost and allows to embed advanced new features into a wide range of devices. To reduce the development effort and to allow to integrate such features easily on your product, we are providing three code examples with our face recognition library in our new function pack. The FP-AI-FaceRig1 is optimized for the STM32 H747 Discovery Kit with add-on camera board using our well-known STM32cube.ai tool set. Now let's see the board and the function pack in action and let me show you its capabilities. When the person approaches the camera, the face is detected and displayed in a red bounding box, which means it is not recognized. Now let's press the blue button and register myself. As you can see, I am enrolled as user zero indicated by a green bounding box. My face is tracked in real time and it is even working if my head is tilted or not fully facing the camera like in my registration picture. We are reaching up to four frames per second for the face detection and recognition processing. Now let's see what happens with a different person. This person is not recognized as registered user indicated by the red box. But we can choose to learn new faces directly on the target by pressing the blue button. Let's do that. The bounding box is turning green and the person is now recognized as user one. On the display, you can also see the match probability. Thanks to artificial intelligence, devices and tools are getting smarter and are getting enhanced with capabilities to provide customized services and make the users life easier. By detecting who is the user of the equipment, devices can customize their behavior to fit user preferences. For example, a user where HVAC can set the thermostat according to user preference. Smart coffee machines can prepare your favorite beverage automatically and even your smart toastle can customize temperature to toast the bread the way you like it. Other use cases are to automate elevators in office buildings or hotels to automatically select the right floor for each person. Or for example, equipment and machines can adapt their display based on user's registered settings or set height and other ergonomic settings based on users registered morphology. These are only a few examples among many possible applications. Face recognition is an effective way to personalize smart devices behavior, display or settings to the user. Thank you for watching.