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<p class="MsoNormal" style="text-align: justify; line-height: 115%;"><span lang="EN-US" style="font-family: 'Times New Roman',serif;">This book provides an overview of current advancements in research related to artificial intelligence (AI), the internet of things (IoT), machine learning (ML), and intelligent computerized systems. It includes state-of-the-art innovative methodologies and real-time examples in a range of the technical fields discussed. The chapters address emerging serious concerns related to wireless networks, sustainability, cybersecurity, deep learning applications within the medical research field, automated intelligent systems, and smart surveillance guidance systems. Additionally, the discussions include reinforcement learning, explainable AI, multilayer deep learning, and optimization defined by experimental results based on benchmark datasets and within real-time environments. Through the integration of theoretical foundations with practical implementation studies, the chapters provide insights into developing scalable, energy-efficient, and secure intelligent systems for future digital environments. Encompassing current research trends within the intelligent data-driven, advanced computational intelligence field, this book will be of a great resource for researchers, industry practitioners, and graduate students.</span></p>

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Proceedings of the 6th International Conference on Artificial Intelligence and Smart Energy

  • 会议论文集

  • 发表日期：

    2026年

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摘要

This book provides an overview of current advancements in research related to artificial intelligence (AI), the internet of things (IoT), machine learning (ML), and intelligent computerized systems. It includes state-of-the-art innovative methodologies and real-time examples in a range of the technical fields discussed. The chapters address emerging serious concerns related to wireless networks, sustainability, cybersecurity, deep learning applications within the medical research field, automated intelligent systems, and smart surveillance guidance systems. Additionally, the discussions include reinforcement learning, explainable AI, multilayer deep learning, and optimization defined by experimental results based on benchmark datasets and within real-time environments. Through the integration of theoretical foundations with practical implementation studies, the chapters provide insights into developing scalable, energy-efficient, and secure intelligent systems for future digital environments. Encompassing current research trends within the intelligent data-driven, advanced computational intelligence field, this book will be of a great resource for researchers, industry practitioners, and graduate students.