Advancing Edge Artificial Intelligence System Contexts

Abstract

Intelligent connectivity at the edge combines wireless communication, edge artificial intelligence (AI), edge computing and internet of things (IoT) technologies to perform machine learning (ML) and deep learning (DL) on connected edge devices. Low latency, ultralowenergy intelligent IoT devices with onboard computing, and a distributed architecture and analytics are essential to drive intelligent connectivity. Intelligent wireless mesh technologies exploit multiple interconnected devices, or nodes, to create a distributed network integrated with edge AI analytics using ML and DL algorithms. In an intelligent wireless mesh network (WMN), each node has embedded intelligence and can communicate directly with its neighbouring nodes and transfer data efficiently to other nodes. Compared with traditional pointtopoint wireless networks, the intelligent wireless mesh approach offers several advantages, including increased coverage, redundancy, scalability and resilience. The convergence of multiple technologies (connectivity, edge AI, IoT, distributed architectures and federated learning) delivers intelligent edge