TITLE:
Beyond the Cloud: Federated Learning and Edge AI for the Next Decade
AUTHORS:
Sooraj George Thomas, Praveen Kumar Myakala
KEYWORDS:
Federated Learning, Edge AI, Decentralized Computing, Privacy-Preserving AI, Blockchain, Quantum AI
JOURNAL NAME:
Journal of Computer and Communications,
Vol.13 No.2,
February
20,
2025
ABSTRACT: As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.