March 2022 Edition: Role of AI in Industry
The IIC's Journal of Innovation - the initiative of our Thought Leadership Task Group - highlights the innovative ideas, approaches, products and services emerging within the industrial internet.
We are excited to bring you this 19th edition of the Journal of Innovation: “The Role of Artificial Intelligence in Industry.” AI is a significant contributor to value creation in the fourth industrial revolution and estimated to provide a $14 trillion boost to the global economy by 2035. The goal of this edition is to illustrate the relevance of AI to Industrial IoT – from its applications to implementation challenges.
The release of this edition coincides with the recent release of the IIC Industrial IoT Artificial Intelligence Framework. The framework highlights the value proposition AI can enable in next-generation industrial IoT systems and addresses the emerging requirements and implementation challenges. We highly encourage you to take a close look at the framework.
We would like to thank the authors and editors of this content, and hope you find it a valuable resource as you consider the application of digital transformation techniques in your organization. As always, your comments are very welcome.
Table of Contents
- Applicative Framework for End-to-End AOI Implementation
This article covers a concrete implementation of an Automatic Optical Inspection (AOI) system including the architecture from hardware and software points of view, and how it has been applied to real manufacturing processes.
Authors: Valerio Di Eugenio, Gianluca Gamba, and Chiara Mattei of Bosch. - Design Considerations and Guidelines for Implementing Federated Learning in Smart Manufacturing Applications
This article describes a common framework to support the development of Federated Learning. This enables the sharing of sensitive data across smart manufacturing organizations.
Authors: Sourabh Bharti and Alan McGibney of Munster Technological University, Cork Ireland, and Tristan O’Gorman of IBM - Securing the ML Lifecycle
This article provides approaches and recommendations on how to secure Machine Learning models throughout their lifecycles.
Authors: Dr. Carmen Kempka, WIBU-SYSTEMS AG, and Prof. Dr. Andreas Schaad, University of Offenburg - DDoS Attack Identification Utilizing Machine Learning in Circumstances Involving Hacked IoT Devices/Insider Assaults
This article illustrates the use of machine learning to identify and counter DDoS attacks involving wireless IoT devices.
Authors: Rani Yadav-Ranjan, Arthur Brisebois, and Serene Banerjee of Ericsson GAIA