By bridging the divide between localized device intelligence and centralized cloud computing, edge artificial intelligence (AI) can transform existing businesses and social paradigms. Extreme real-time data processing, enhanced privacy, and decreased latency are among the capabilities. To comprehend how edge AI interacts with hybrid systems that result in full integration with cloud computing, this paper thoroughly examines the whole architecture and important technologies utilized in this technology. Autonomous driving, smart cities, healthcare diagnostics, and the next-generation IoT ecosystems might all be transformed by edge AI. Factors including limited processing capacity, energy, and modelling precision hinder its widespread implementation. These novel strategies were tried in this study, and the results showed a considerable improvement in performance. The findings demonstrated that AI from edge has the potential to transform a wide range of sectors, including healthcare and self driving automobiles. The research’s objective is to provide stakeholders with a comprehensive grasp of edge AI’s potential so they can capitalize on its revolutionary potential for long-term innovation. To create a smarter, more interrelated society, the paper views edge intelligence as a key component of the latest industrial revolution, encouraging scientists, decision-makers, and innovators to embrace and push the boundaries of edge intelligence.

Keywords: Edge AI, artificial intelligence, machine learning, IoT, edge computing, data protection,
model optimization, fog computing, cloud computing, energy efficiency, autonomous systems, smart
healthcare

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