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Narges Mehran presented at HiPEAC Student Challenge IX: IoT for everyone

Title: A Traffic-sign recognition IoT-based Application
Authors: Narges Mehran, Dragi Kimovski, Zahra Najafabadi Samani, Radu Prodan
The work “A Traffic-sign recognition IoT-based Application” got granted for the presentation in the HiPEAC IoT challenge during CSW Spring 2022.
International data corporation predicts that 21.5  billion connected Internet of Things (IoT) devices will generate 55% of all data by 2025. Nowadays, camera sensors can be embedded in most devices. Therefore, we designed an application to receive a video stream from a camera sensor and perform the video processing. First our designed application pre-processes the sensed data by two high-quality video encoding and framing frameworks. Afterward, we apply the machine learning  (ML) model based on the low and high training accuracies. Because the user devices cannot often perform high-load machine learning training operations, we consider the ML inference operation acting as a lightweight trained ML model. At the end, the processed data is packaged for the consumer such as the driver of a car.