Generative Digital Twins: A Novel Approach in the IoT Edge-Cloud Continuum
This paper introduces the concept of Generative Digital Twins (GDTs), an evolution of Digital Twins (DTs) that incorporates Generative AI to enhance prediction, control, optimization, and simulation capabilities. Originating in the manufacturing sector, DTs have been revitalized by advancements in IoT and AI, allowing them to interact with real-world data and achieve their goals more effectively. The paper defines GDTs, explores how Generative AI bridges model- and data-driven approaches, and highlights its benefits in IoT environments, particularly within Smart City scenarios where predictive accuracy, system robustness, and explainability are crucial.
Aug 16, 2024
Opportunistic Digital Twin: an Edge Intelligence enabler for Smart City
The paper discusses the importance of Digital Twins (DTs) enhanced by AI, Edge Computing, and IoT. It introduces the concept of "opportunistic" interpretation of DTs, creating dynamic digital replicas of physical objects through AI at the network edge. This approach is demonstrated through a traffic prediction use case, highlighting improved performance and resource efficiency.
Aug 18, 2023
Disclosing Edge Intelligence: A Systematic Meta-Survey
Edge Intelligence (EI) is a new solution for improving IoT services by overcoming cloud computing limitations. To analyze this field, this paper provides a systematic analysis of existing studies using the PRISMA methodology. The paper outlines research questions to explore the past, present, and future directions of EI, as well as its relationship with IoT and cloud computing.
Mar 2, 2023