Название: AI-Driven IoT Systems for Industry 4.0
Автор: Deepa Jose, Preethi Nanjundan, Sanchita Paul, Sachi Nandan Mohanty
Издательство: CRC Press
Серия: Edge AI in Future Computing
Год: 2025
Страниц: 419
Язык: английский
Формат: pdf (true)
Размер: 15.6 MB

The purpose of this book is to discuss the trends and key drivers of Internet of Things (IoT) and Artificial Intelligence (AI) for automation in Industry 4.0. IoT and AI are transforming the industry thus accelerating efficiency and forging a more reliable automated enterprise. AI-driven IoT systems for Industry 4.0 explore current research to be carried out in the cutting-edge areas of AI for advanced analytics, integration of industrial IoT (IIoT) solutions and Edge components, automation in cyber-physical systems, world leading Industry 4.0 frameworks and adaptive supply chains, etc.

A thorough exploration of Industry 4.0 is provided, focusing on the challenges of digital transformation and automation. It covers digital connectivity, sensors, and the integration of intelligent thinking and data science. Emphasizing the significance of AI, the chapter delves into optimal decision-making in Industry 4.0. It extensively examines automation and hybrid edge computing architecture, highlighting their applications. The narrative then shifts to IIoT and edge AI, exploring their convergence and the use of edge AI for visual insights in smart factories. The book concludes by discussing the role of AI in constructing digital twins, speeding up product development lifecycles, and offering insights for decision-making in smart factories. Throughout, the emphasis remains on the transformative impact of deep learning and AI in automating and accelerating manufacturing processes within the context of Industry 4.0.

The hand is a human organ used to manipulate physical objects. For this reason, the hand is most commonly used by humans to communicate and operate machines. The process of comprehending and classifying significant hand movements made by humans is known as hand gesture recognition. The mouse and keyboard are the basic inputs and outputs of a computer, and you need to use your hands to use both of these devices. The most important and immediate exchange of information between humans and machines takes place through visual and audio aids, but this communication is one-way. Hand gestures support everyday communication to clearly convey our message. In this project, the detection of hands will be done using Python programming and TensorFlow libraries. Applying the ideas of hand classification and the hand detection system will allow for the development of hand gesture recognition using Python and OpenCV. This project titled “Object Detection Using TensorFlow” comes under an AI-based project. TensorFlow, OpenCV, LabelImg, Python programming, and other tools were used to develop this project.

This book is intended for undergraduates, postgraduates, academicians, researchers, and industry professionals in industrial and computer engineering.