EDGE INTELLIGENCE IN IOT: ENABLING SMARTER, FASTER AUTONOMOUS DEVICES THROUGH ARTIFICIAL INTELLIGENCE AND EDGE COMPUTING

Abstract

The intersection of Edge Computing and Artificial Intelligence represented by Edge Intelligence (EI) is paving a new road for the Internet of Things (IoT), eliminating its main shortcoming, i.e. the latency, the bandwidth constraints, and the privacy concerns of the traditional cloud systems. In this paper, we have discussed principles, challenges and applications of EI, focusing on its overall contribution to real-time secure and energy-efficient operations in healthcare, smart cities, industrial IOT and autonomous vehicles. Federated learning, lightweight AI models, and hybrid edge-cloud architectures are analyzed on the grounds of their key technological advancement on how energy and scalability restrictions can be overcome. Finally, integration of 6G networks with blockchain technology along with an ethical AI framework is proposed as a path to enable future capabilities. This work intends to point researchers, developers, and policymakers in the direction of adopting security and sustainability in EI system by providing a comprehensive survey of the available solutions and future trends.