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      Book

      Artificial Intelligence Techniques in IoT Sensor Networks
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      Book

      Artificial Intelligence Techniques in IoT Sensor Networks

      DOI link for Artificial Intelligence Techniques in IoT Sensor Networks

      Artificial Intelligence Techniques in IoT Sensor Networks book

      Artificial Intelligence Techniques in IoT Sensor Networks

      DOI link for Artificial Intelligence Techniques in IoT Sensor Networks

      Artificial Intelligence Techniques in IoT Sensor Networks book

      Edited ByMohamed Elhoseny, K. Shankar, Mohamed Abdel-Basset
      Edition 1st Edition
      First Published 2020
      eBook Published 18 December 2020
      Pub. Location New York
      Imprint Chapman and Hall/CRC
      DOI https://doi.org/10.1201/9781003007265
      Pages 231
      eBook ISBN 9781003007265
      Subjects Computer Science, Engineering & Technology
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      Elhoseny, M., Shankar, K., & Abdel-Basset, M. (Eds.). (2020). Artificial Intelligence Techniques in IoT Sensor Networks (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781003007265

      ABSTRACT

      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.

      TABLE OF CONTENTS

      chapter 1|17 pages

      Adaptive Regularized Gaussian Kernel FCM for the Segmentation of Medical Images

      An Artificial Intelligence-Based IoT Implementation for Teleradiology Network
      ByS. N. Kumar, A. Lenin Fred, L. R. Jonisha Miriam, H. Ajay Kumar, Parasuraman Padmanabhan, Balazs Gulyas

      chapter 2|16 pages

      Artificial Intelligence-Based Fuzzy Logic with Modified Particle Swarm Optimization Algorithm for Internet of Things-Enabled Logistic Transportation Planning

      ByPhong Thanh Nguyen

      chapter 3|15 pages

      Butterfly Optimization-Based Feature Selection with Gradient Boosting Tree for Big Data Analytics in Social Internet of Things

      ByIrina V. Pustokhina, Denis A. Pustokhin

      chapter 4|16 pages

      An Energy-Efficient Fuzzy Logic-Based Clustering with Data Aggregation Protocol for WSN-Assisted IoT System

      ByTran Hoang Vu, Gianhu Nguyen

      chapter 5|15 pages

      Analysis of Smart Home Recommendation System from Natural Language Processing Services with Clustering Technique

      ByN. Krishnaraj, R. Lenin Babu, R. Adaline Suji, Andino Maseleno

      chapter 6|16 pages

      Metaheuristic-Based Kernel Extreme Learning Machine Model for Disease Diagnosis in Industrial Internet of Things Sensor Networks

      ByS. Dhanasekaran, I. S. Hephzi Punithavathi, P. Duraipandy, A. Sivanesh Kumar, P. Vijayakarthik, S. Rajasekaran, B. S. Murugan

      chapter 7|13 pages

      Fuzzy Support Vector Machine with SMOTE for Handling Class Imbalanced Data in IoT-Based Cloud Environment

      ByA. Francis Saviour Devaraj, P. Vijayakarthik, S. Dhanasekaran, G. Murugaboopathi, B.S. Murugan

      chapter 8|21 pages

      Energy-Efficient Unequal Clustering Algorithm Using Hybridization of Social Spider with Krill Herd in IoT-Assisted Wireless Sensor Networks

      ByR. Buvanesvari, A. Rijuvana Begum

      chapter 9|15 pages

      IoT Sensor Networks with 5G-Enabled Faster RCNN-Based Generative Adversarial Network Model for Face Sketch Synthesis

      ByN. Gnanasankaran, E. Ramaraj

      chapter 10|16 pages

      Artificial Intelligence-Based Textual Cyberbullying Detection for Twitter Data Analysis in Cloud-Based Internet of Things

      BySrikanth Cherukuvada, Kiranmai Bellam, A. Soujanya, N. Krishnaraj

      chapter 11|13 pages

      An Energy-Efficient Quasi-Oppositional Krill Herd Algorithm-Based Clustering Protocol for Internet of Things Sensor Networks

      ByK.M. Baalamurugan, R. Gopal, D. Vinotha, A. Daniel, Vijay Ramalingam

      chapter 12|15 pages

      An Effective Social Internet of Things (SIoT) Model for Malicious Node Detection in Wireless Sensor Networks

      ByVijay Ramalingam, Dinesh Babu Mariappan, R. Gopal, K.M. Baalamurugan

      chapter 13|16 pages

      IoT-Based Automated Skin Lesion Detection and Classification Using Gray Wolf Optimization with Deep Neural Network

      ByA. Daniel, S. Venkatraman, Srinath Doss, Bhanu Chander Balusa, Andino Maseleno, K. Shankar
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