2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 10 , Issue 2 , PP: 18-23, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Luis Freire Lescano 1 * , Marcos Lalama Flores 2 , Maria Pico Pico 3
Doi: https://doi.org/10.54216/JISIoT.100202
In the rapidly evolving landscape of the Visual Internet of Things (VIoT), this paper presents a pioneering approach to distributed facial expression recognition—an intelligent system that holds transformative potential for security, human-computer interaction, and personalized services. Our journey unfolds with the development of the Light Vision Transformer (LVT) model, specifically engineered to operate on the resource-constrained edges of the VIoT network. Differentially private federated training ensures both the model's prowess and the preservation of user privacy. Through meticulous experimental evaluations, we validate the effectiveness and efficiency of our approach, shedding light on its scalability and ethical implications. This work is more than a technical endeavor; it symbolizes a commitment to responsible AI, balancing innovation with the preservation of individual rights. Our findings resonate beyond facial expression recognition, serving as a beacon for the VIoT community to explore the dynamic interplay between distributed computing, edge intelligence, and ethical considerations. As we stride towards a more connected and responsive world, this research paves the way for continued exploration, propelling VIoT technology towards a future that is both intelligent and ethically attuned.
Facial Recognition , Visual Internet of Things (VIoT) , Distributed Computing , Intelligent Systems , Edge Computing , Internet of Things (IoT) , Distributed Systems , Edge Devices , VIoT Applications , VIoT Architecture.
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