Edge computing, coupled with Artificial Intelligence (AI), represents a paradigm shift in data processing, enabling real-time analytics and decision-making at the source. By distributing computation closer to the data origin, this integration addresses the critical challenges of latency, bandwidth, and privacy, which traditional cloud-centric systems face. AI algorithms deployed on Edge devices enable localized intelligence, facilitating transformative advancements in domains such as healthcare, smart cities, industrial automation, and autonomous systems. This review comprehensively examines the synergistic relationship between AI and Edge computing, highlighting key applications, challenges, and future research opportunities. Moreover, we emphasize the critical need for lightweight AI models, energy-efficient systems, and robust security measures to fully harness the potential of Edge AI in an increasingly connected world.
Dintakurthy et al. (Sat,) studied this question.