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    1. Data och IT
    2. Hårdvara
    • Nyhet

    Advances in Artificial Intelligence and Smart Environments: Proceedings of ICAISE 2025

    Volume 3

    AvYousef Farhaoui,Hamed Taherdoost

    Häftad, Engelska, 2026

    Del 2171 i serien Lecture Notes in Networks and Systems

    2 563 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    This book provides a comprehensive collection of recent research addressing practical and emerging challenges in intelligent technologies and smart environments. It highlights innovative methods, real-world applications, and interdisciplinary solutions that support the development of intelligent systems capable of improving efficiency, sustainability, and decision-making in modern digital ecosystems.This book brings together contributions that explore advanced approaches in artificial intelligence, data analytics, machine learning, Internet of Things (IoT), smart cities, cybersecurity, and intelligent automation. By presenting both theoretical developments and applied research, this book offers insights into how intelligent technologies can be designed, optimized, and deployed to solve complex problems in areas such as transportation, healthcare, energy management, environmental monitoring, and urban infrastructure.A distinctive aspect of this work is its focus on integrating artificial intelligence techniques with smart environment applications, emphasizing scalable, data-driven, and human-centered solutions. This book highlights novel algorithms, hybrid models, and intelligent architectures that address issues related to efficiency, sustainability, and digital transformation. This book also presents case studies and experimental frameworks that demonstrate the practical impact of these technologies in real-world scenarios.This book has a broad scope covering topics such as intelligent data processing, predictive analytics, computer vision, deep learning systems, smart sensing technologies, and decision-support platforms. By combining methodological advances with application-oriented research, the book provides a balanced perspective on both the scientific and practical aspects of intelligent systems.This book is intended for researchers, academics, graduate students, engineers, and industry practitioners interested in artificial intelligence and smart environments. It serves as a valuable reference for those working in interdisciplinary domains where intelligent technologies are applied to improve system performance, automation, and digital services.

    Produktinformation

    • Utgivningsdatum:2026-08-07
    • Mått:155 x 235 x 41 mm
    • Vikt:1 136 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Lecture Notes in Networks and Systems
    • Antal sidor:748
    • Förlag:Springer Nature Switzerland AG
    • ISBN:9783032280961

    Utforska kategorier

    • Hårdvara inom Data och IT
    • Databaser inom Data och IT
    • Artificiell intelligens inom Data och IT

    Innehållsförteckning

    • Framework for Visual Data Quality Control in Retail Systems.- DCGAN-IDS: A Deep Convolutional Generative Adversarial Network Framework for Intrusion Detection in Network Security.- Assessing Risks and Privacy Challenges in the Artificial Intelligence Era.- Artificial intelligence and smart healthcare a bibliometric mapping of the field.- Benchmarking Forecasting Techniques for Direct Normal Irradiance: A Comparative Study.- Bio Track: Wireless Wearable Health Monitoring Device.- Stock Investment Portfolio Construction using Machine Learning.- Optimization of Low-Carbon Concrete Mix Design Based Machine Learning : A Data-Driven Approach.- AI-DRIVEN TRANSFER PRICING ANALYTICS AND DISPUTE RESOLUTION IN THE DIGITAL ECONOMY: INTEGRATINGBIG DATA and INTELLIGENT SYSTEMS for FISCAL JUSTICE.- IoT Device: Attack Classification and their Anomaly Detection through Machine Learning Algorithm.- Enhanced Arabic Handwritten Character Recognition Using Hybrid VGG16–VGG19 Deep Feature Fusion with a K-NN Classifier.- Transformer-Based Attention Mechanisms in Agricultural Deep Learning: From Self-Attention to Cross-Modal Fusion.