Edge artificial intelligence is a research concept and methodological approach focused on executing artificial intelligence tasks directly on local devices or nodes at the "edge" of a network, rather than relying solely on centralized cloud infrastructure. This field investigates the development, deployment, and optimization of AI models and algorithms for resource-constrained, distributed environments, emphasizing key characteristics such as low latency, enhanced privacy, reduced bandwidth usage, and computational efficiency. Its significance lies in enabling real-time processing, supporting autonomous systems, and facilitating scalable, distributed intelligence critical for applications ranging from IoT and robotics to industrial automation and pervasive computing.