Artificial Intelligence Techniques in IoT Sensor Networks

Artificial Intelligence Techniques in IoT Sensor Networks
PDF
  • eBook:
    Artificial Intelligence Techniques in IoT Sensor Networks
  • Author:
    Mohamed Elhoseny, K Shankar, Mohamed Abdel-Basset
  • Edition:
    1 edition
  • Categories:
  • Data:
    December 29, 2020
  • ISBN:
    0367439255
  • ISBN-13:
    9780367439255
  • Language:
    English
  • Pages:
    231 pages
  • Format:
    PDF

Book Description
Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book is intended to develop a shared understanding of applications of AI techniques in the present and near term. The book maps the technical impacts of AI technologies, applications and their implications on the design of solutions for sensor networks.
This text introduces researchers and aspiring academicians to the latest developments and trends in AI applications for sensor networks in a clear and well-organized manner. It is mainly useful for research scholars in sensor networks and AI techniques. In addition, professionals and practitioners working on the design of real-time applications for sensor networks may benefit directly from this book. Moreover, graduate and master’s students of any departments related to AI, IoT and sensor networks can find this book fascinating for developing expert systems or real-time applications.
This book is written in a simple and easy language, discussing the fundamentals, which relieves the requirement of having early backgrounds in the field. From this expectation and experience, many libraries will be interested in owning copies of this work.

Content

Chapter 1. Adaptive Regularized Gaussian Kernel FCM for the Segmentation of Medical Images
Chapter 2. Artificial Intelligence-Based Fuzzy Logic with Modified Particle Swarm Optimization Algorithm for Internet of Things-Enabled Logistic Transportation Planning
Chapter 3. Butterfly Optimization-Based Feature Selection with Gradient Boosting Tree for Big Data Analytics in Social Internet of Things
Chapter 4. An Energy-Efficient Fuzzy Logic-Based Clustering with Data Aggregation Protocol for WSN-Assisted IoT System
Chapter 5. Analysis of Smart Home Recommendation System from Natural Language Processing Services with Clustering Technique
Chapter 6. Metaheuristic-Based Kernel Extreme Learning Machine Model for Disease Diagnosis in Industrial Internet of Things Sensor Networks
Chapter 7. Fuzzy Support Vector Machine with SMOTE for Handling Class Imbalanced Data in IoT-Based Cloud Environment
Chapter 8. Energy-Efficient Unequal Clustering Algorithm Using Hybridization of Social Spider with Krill Herd in IoT-Assisted Wireless Sensor Networks
Chapter 9. IoT Sensor Networks with 5G-Enabled Faster RCNN-Based Generative Adversarial Network Model for Face Sketch Synthesis
Chapter 10. Artificial Intelligence-Based Textual Cyberbullying Detection for Twitter Data Analysis in Cloud-Based Internet of Things
Chapter 11. An Energy-Efficient Quasi-Oppositional Krill Herd Algorithm-Based Clustering Protocol for Internet of Things Sensor Networks
Chapter 12. An Effective Social Internet of Things (SIoT) Model for Malicious Node Detection in Wireless Sensor Networks
Chapter 13. IoT-Based Automated Skin Lesion Detection and Classification Using Gray Wolf Optimization with Deep Neural Network

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