Operationalize Edge AI for Next-Generation IoT Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 57
Special Issue Editors
Interests: edge AI; edge computing; MLOps; TinyMLOps; IoT; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: distributed AI; federated learning explainable AI; internet of things (IoT)
Special Issue Information
Dear Colleagues,
The Internet of Things (IoT) has become an integral part of our lives, enabling efficient, scalable, and intelligent systems. In parallel, Edge AI has emerged as a transformative technology for the next generation of smart IoT applications. By processing data locally on devices, Edge AI reduces latency, minimizes energy consumption, and enhances privacy, making it particularly well suited for resource-constrained environments. Beyond embedded devices, Edge AI extends to powerful computing platforms deployed at the edge of the network, driving innovation across a wide range of applications.
This Special Issue highlights the critical role of Edge AI in enabling more intelligent and adaptive IoT systems. Topics of interest include advancements in TinyML for deploying AI models on edge devices, innovations in MLOps for scalable AI operations, and novel architectures for distributed AI in IoT ecosystems. Contributions that showcase real-world applications, such as in smart cities, healthcare, agriculture, and industrial automation, are particularly welcome. Additionally, this Special Issue explores the challenges of developing sustainable and secure Edge AI solutions, bridging the gap between centralized and distributed intelligence. We invite researchers, practitioners, and industry experts to share their insights and advancements in shaping the future of IoT through Edge AI technologies.
Dr. Mattia Antonini
Dr. Fabrizio Ruffini
Dr. Michela Fazzolari
Guest Editors
Manuscript Submission Information
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Keywords
- edge AI
- internet of things (IoT)
- TinyML
- MLOps
- cloud-to-thing continuum
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