Another use case of REBECCA involves an AI-powered fridge developed by Arcelik. In this scenario, the fridge is equipped with two cameras: one mounted on the door, capturing the interior, and the other inside the body, capturing the door. When the door is opened, these cameras are triggered to capture multiple image frames until the door is closed again. Among these frames, the best ones, which provide optimal visibility of the fridge interior, are selected using a TOF sensor that measures the distance between the door and the body. The selected pairs of images are then transferred to the cloud for image processing and analysis, after which they are sent to the related users' Arcelik-specific mobile application (HomeWhiz™) for remote monitoring of the fridge interior.

In the current cloud-based architecture of this use case, all image processing algorithms and AI-based computer vision models, including object recognition, human detection, distortion removal, and cropping algorithms, run on the cloud platform. The object recognition model identifies and localizes 33 different objects, such as eggs, milk, water, apples, and more, creating an inventory list. The human detection model checks if there is a human in an image, which may occur unintentionally, and deletes such images if any are found due to privacy reasons. As part of the REBECCA project, edge versions of these AI models are being developed. These edge versions will initially be deployed, executed and evaluated on REBECCA emulators and eventually User interface of the HomeWhiz™ mobile application integrated into REBECCA chips.

As part of the REBECCA project, edge versions of these AI models are being developed. These edge versions will initially be deployed, executed and evaluated on REBECCA emulators and eventually User interface of the HomeWhiz™ mobile application integrated into REBECCA chips.

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