Iot Enabled Convolutional Neural Networks Techniques And Applications


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IoT-enabled Convolutional Neural Networks: Techniques and Applications


IoT-enabled Convolutional Neural Networks: Techniques and Applications

Author: Mohd Naved

language: en

Publisher: CRC Press

Release Date: 2023-05-08


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Convolutional neural networks (CNNs), a type of deep neural network that has become dominant in a variety of computer vision tasks, in recent years, CNNs have attracted interest across a variety of domains due to their high efficiency at extracting meaningful information from visual imagery. CNNs excel at a wide range of machine learning and deep learning tasks. As sensor-enabled internet of things (IoT) devices pervade every aspect of modern life, it is becoming increasingly critical to run CNN inference, a computationally intensive application, on resource-constrained devices. Through this edited volume, we aim to provide a structured presentation of CNN-enabled IoT applications in vision, speech, and natural language processing. This book discusses a variety of CNN techniques and applications, including but not limited to, IoT enabled CNN for speech denoising, a smart app for visually impaired people, disease detection, ECG signal analysis, weather monitoring, texture analysis, etc. Unlike other books on the market, this book covers the tools, techniques, and challenges associated with the implementation of CNN algorithms, computation time, and the complexity associated with reasoning and modelling various types of data. We have included CNNs' current research trends and future directions.

Computational Intelligence for Analysis of Trends in Industry 4.0 and 5.0


Computational Intelligence for Analysis of Trends in Industry 4.0 and 5.0

Author: Joseph Bamidele Awotunde

language: en

Publisher: CRC Press

Release Date: 2025-06-17


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Industry 4.0 and Industry 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency. Computational Intelligence for Analysis of Trends in Industry 4.0 and 5.0 examines the trends in applications that merge three key disciplines: Computational Intelligence (CI), Industry 4.0, and Industry 5.0. It presents solutions using industrial Internet of Things (IIoT) technologies, augmented by CI-based techniques, modeling, controls, estimations, applications, systems, and future scopes. These applications use data from smart sensors, processed through enhanced CI methods, to make smart automation more effective. Industry 4.0 integrates data and intelligent automation into manufacturing, using technologies like CI, Internet of Things (IoT), IIoT, and cloud computing. It transforms data into actionable insights for decision-making and process optimization, essential for modern competitive businesses managing high-speed data integration in production processes. Currently, Industry 4.0 and Industry 5.0 are undergoing significant transformations due to advances in applying artificial intelligence (AI), big data analytics, telecommunication technologies, and control theory. These trends are increasingly multidisciplinary, integrating mechanical, control, and information technologies. However, they face technical challenges such as parametric uncertainties, external disturbances, sensor noise, and mechanical failures. To address these issues, this book examines trends such as CI technologies as fuzzy logic, neural networks, and reinforcement learning and their application to modeling, control, and estimation. It also covers recent advancements in IIoT sensors, microcontrollers, and big data analytics that further enhance CI-based solutions in Industry 4.0 and Industry 5.0 systems.

AI Applications for Business, Medical, and Agricultural Sustainability


AI Applications for Business, Medical, and Agricultural Sustainability

Author: Naim, Arshi

language: en

Publisher: IGI Global

Release Date: 2024-03-07


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Climate change, natural resource depletion, and unsustainable agricultural practices pose unprecedented challenges to our planet. The increasing environmental footprint of computer networks, communication systems, and other IT infrastructures exacerbates these issues, contributing significantly to energy consumption and greenhouse gas emissions. Without innovative solutions, these challenges will continue to escalate, threatening the sustainability of our planet for future generations. AI Applications for Business, Medical, and Agricultural Sustainability offers a comprehensive solution by harnessing the power of Artificial Intelligence (AI) and High-Performance Computing (HPC). This book is ideal for educators, environmentalists, industry professionals, researchers, and academics. By introducing new energy models, algorithms, and methodologies, the book provides a roadmap for developing next-generation computing and communication infrastructures that are environmentally sustainable.