The Future of Edge AI: Combining Artificial Intelligence with Edge Computing

Abstract

The recent rapid evolution of the Artificial Intelligence (AI) and Edge Computing resulted in the advent of the new technological paradigm of the Edge AI, which brings the intelligence closer to the location of the data sources, which offers real-time analytics, enables making decisions in less time, and offers more privacy. Unlike the previous system of cloud based AI (relying on the central processing unit), Edge AI is decentralized and introduces machine learning into the peripheral devices, such as sensors, smartphones, and Internet of Things units. In this paper, the future of Edge AI, its application and issues associated with the current industries, such as healthcare, manufacturing, transportation, and smart cities will be discussed. The study shows that Edge AI reduces the time of latency, optimizes the use of bandwidth and generates greater autonomy in the system, and incorporates the concerns of privacy and power consumption. In addition, the 5G networks and neuromorphic computing, combined together, will make an Edge AI system implementation and operation faster. The findings show that Edge AI will play a significant role in designing intelligent ecosystems since it would offer sustainable and responsive infrastructures across various regions in accordance with the trends of worldwide digital transformation.