Artificial Intelligence Techniques in IoT Sensor Networks

Faculty Computer Science Year: 2021
Type of Publication: ZU Hosted Pages:
Authors:
Journal: 9780367439255 Taylor and Francis Volume:
Keywords : Artificial Intelligence Techniques , , Sensor Networks    
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.
   
     
 
       

Author Related Publications

  • Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019 More
  • Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014 More
  • Mohammed Abdel Basset Metwally Attia, "A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems", Springer London, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection", Pergamon, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations", Pergamon, 2021 More

Department Related Publications

  • Saber Mohamed, "Evolving the Parameters of Differential Evolution using Evolutionary Algorithms", Springer, 2014 More
  • Saber Mohamed, "A Comparative Study of Different Variants of Genetic Algorithms for Constrained Optimization", Springer, 2010 More
  • Saber Mohamed, "Differential Evolution with Multiple Strategies for Solving CEC2011 Real-world Numerical Optimization Problems", IEEE, 2011 More
  • Mohammed Abdel Basset Metwally Attia, "A Review on the Applications of Neutrosophic Sets", Source: Journal of Computational and Theoretical Nanoscience, Volume 13, Number 1, January 2016, pp. 936-944(9), 2016 More
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