LAUSR

EMERGING from decades of automation, connectivity, and instrumentation, the intelligent edge has evolved into a revolutionary set of proficiencies that are already reshaping many of the leading communication companies and the latest technology on the planet. To propel the world’s latest technology companies so as to help accelerate the Industrial Internet-of-Things (IIoT) revolution toward next-generation operational efficiency and computing connectivity, the intelligent edge expands the frontier for faster, less expensive, and more secure operations from robotics systems to virtual reality to Internet-of-Things (IoT) [A1], [A2]. There have been various exciting developments in the latest technology that may contribute to improving the robustness of IIoT services like automated manufacturing, industrial monitoring, shipping, artificial intelligence (AI), and data analytics [A3], [A4]. The development and adoption of intelligent edge computing methodologies to support fast response time, low latency, and efficient use of visibility and bandwidth is, however, a challenge. The reason is that intelligent edge is a cloud-to-edge architecture where some components which run on centralized clouds cause severe security and storage issues [A5], [A6]. In addition, the way computations operate on various parts of the data journey may further affect the speed of services on various distributed architecture based on their needs. There are certain best practices and standard issues with the security and interoperability that remain yet to be focused on. Therefore, sophisticated intelligent edge schemes are required that are able to provide integration of data across multiple sectors with coordination and effective implementation capabilities [A7], [A8]. The major challenge to an intelligent edge approach is in predicting the accuracy and expressiveness while computing simultaneously. Neural networks along with the AI methods have shown noticeably better performance in comparison to their conventional counterparts in terms of the accuracy of the outcomes. However, it also brings more interoperability and complexity issues and hence, arise serious challenges regarding the validity and verifiability of these approaches. Thus, this Special Issue propose to share new ideas, recent findings, and state-of-the-art solutions related to the integration of edge intelligence with IIoT. This Special Section has received a huge response from the community and 19 articles are eventually accepted based upon the quality, novelty, and