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Artificial Intelligence Techniques in IoT Sensor Networks.

By: Contributor(s): Material type: TextTextSeries: Chapman and Hall/CRC Distributed Sensing and Intelligent Systems SeriesPublisher: Milton : CRC Press LLC, 2020Copyright date: ©2022Edition: 1st edDescription: 1 online resource (232 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781000318821
Subject(s): Genre/Form: Additional physical formats: Print version:: Artificial Intelligence Techniques in IoT Sensor NetworksDDC classification:
  • 006.3
LOC classification:
  • TK7872.D48 .E446 2021
Online resources:
Contents:
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- About the Editors -- Chapter 1: Adaptive Regularized Gaussian Kernel FCM for the Segmentation of Medical Images: An Artificial Intelligence-Based IoT Implementation for Teleradiology Network -- 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 -- Index.
Summary: This book explores the frontiers and challenges of applying Artificial Intelligence (AI) techniques to Sensor Networks. It covers how sensor networks are widely used to collect environmental parameters in homes, buildings, vehicles, etc., and how they are used as a source of information to aid decision-making processes.
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Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- About the Editors -- Chapter 1: Adaptive Regularized Gaussian Kernel FCM for the Segmentation of Medical Images: An Artificial Intelligence-Based IoT Implementation for Teleradiology Network -- 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 -- Index.

This book explores the frontiers and challenges of applying Artificial Intelligence (AI) techniques to Sensor Networks. It covers how sensor networks are widely used to collect environmental parameters in homes, buildings, vehicles, etc., and how they are used as a source of information to aid decision-making processes.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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