  The digital landscape of the Internet of Energy (IoE) is on the brink of a
revolutionary transformation with the integration of edge Artificial
Intelligence (AI). This comprehensive review elucidates the promise and
potential that edge AI holds for reshaping the IoE ecosystem. Commencing with a
meticulously curated research methodology, the article delves into the myriad
of edge AI techniques specifically tailored for IoE. The myriad benefits,
spanning from reduced latency and real-time analytics to the pivotal aspects of
information security, scalability, and cost-efficiency, underscore the
indispensability of edge AI in modern IoE frameworks. As the narrative
progresses, readers are acquainted with pragmatic applications and techniques,
highlighting on-device computation, secure private inference methods, and the
avant-garde paradigms of AI training on the edge. A critical analysis follows,
offering a deep dive into the present challenges including security concerns,
computational hurdles, and standardization issues. However, as the horizon of
technology ever expands, the review culminates in a forward-looking
perspective, envisaging the future symbiosis of 5G networks, federated edge AI,
deep reinforcement learning, and more, painting a vibrant panorama of what the
future beholds. For anyone vested in the domains of IoE and AI, this review
offers both a foundation and a visionary lens, bridging the present realities
with future possibilities.
