The Today and Future of WSN, AI, and IoT PDF Download

Author: Chandrakant Naikodi
Publisher: BPB Publications
ISBN: 9389845165
Category : Computers
Languages : en
Pages : 320

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Book Description
Doors are never locked for smart software and smart devices that are trained by smart people KEY FEATURESÊÊ - A book for everyone interested to know more about WSN, AI, and IoT - Discover various Open source tools & techniques for research and development in these felidsÊÊ - An easy-to-understand guide that will help you get familiar with the upcoming developments in WSN, AI, and IoT DESCRIPTIONÊÊ Almost every industry is looking for solutions for the best performance in the work that they produce. Researchers and developers are developing promising solutions that address the industrial problems to increase the effectiveness and efficiency of either the product or the service. This paradigm has changed the way many solutions and services are designed. Wireless Sensor Networks (WSN) are the backbone implementation for the Internet of Things (IoT) to be realized. For the IoT to produce efficient results, Artificial Intelligence (AI) becomes the key assistance; however, it needs careful modeling.Ê The content for the book is planned and prepared in such a way that you will be able to understand the concept and can interpret it for their use. The concepts, technologies, processes that are discussed in the book are contemporary and futuristic. Every chapter is well planned to be a subsequent chapter for the previous. In the Summary section of each chapter, there are a few review questions and a case for research.Ê WHAT WILL YOU LEARN - Learn about the most popular AI & IoT research topics - Discover a few WSN, IoT and AI Simulators - Get to know more about the fusion of Blockchain and IoT technologies - Know more about the AI and IoT predictions in the global scenarioÊ - Become aware of the various multi-disciplinary research based on WSN, AI, and IoT WHO THIS BOOK IS FORÊÊ By nature, every human is anxious to learn and would be benefited when they find the right direction. This book is truly intended for all students, teachers, product designers, opensource developers. However, it does not limit them alone. Those who have stepped into research, afresh, will find this book a more exciting one. TABLE OF CONTENTS 1. Introduction 2. WSN, AI, and IoT: Future Shock 3. Active Research Areas of WSN, AI, and IoT 4. Simulators of WSN, AI, and IoT 5. Blockchain for WSN, AI, and IoT 6. What is Next? 7. State of AI and IoT by 2050

Author: Abhinav Sharma
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110734656
Category : Computers
Languages : en
Pages : 239

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Book Description
This book focuses on artificial intelligence in the field of digital signal processing and wireless communication. The implementation of machine learning and deep learning in audio, image, and video processing is presented, while adaptive signal processing and biomedical signal processing are also explored through DL algorithms, as well as 5G and green communication. Finally, metaheuristic algorithms of related mathematical problems are explored.

Author: Soumya Ranjan Nayak
Publisher: CRC Press
ISBN: 1000458512
Category : Computers
Languages : en
Pages : 263

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Book Description
Smart Sensor Networks (WSNs) using AI have left a mark on the lives of all by aiding in various sectors, such as manufacturing, education, healthcare, and monitoring of the environment and industries. This book covers recent AI applications and explores aspects of modern sensor technologies and the systems needed to operate them. The book reviews the fundamental concepts of gathering, processing, and analyzing different AI-based models and methods. It covers recent WSN techniques for the purpose of effective network management on par with the standards laid out by international organizations in related fields and focuses on both core concepts along with major applicational areas. The book will be used by technical developers, academicians, data sciences, industrial professionals, researchers, and students interested in the latest innovations on problem-oriented processing techniques in sensor networks using IoT and evolutionary computer applications for Industry 4.0.

Author: Ajith Abraham
Publisher: Springer
ISBN: 3319477153
Category : Technology & Engineering
Languages : en
Pages : 220

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Book Description
This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems. The book serves as a guide for surveying several state-of-the-art WSN scenarios in which CI approaches have been employed. The reader finds in this book how CI has contributed to solve a wide range of challenging problems, ranging from balancing the cost and accuracy of heterogeneous sensor deployments to recovering from real-time sensor failures to detecting attacks launched by malicious sensor nodes and enacting CI-based security schemes. Network managers, industry experts, academicians and practitioners alike (mostly in computer engineering, computer science or applied mathematics) benefit from th e spectrum of successful applications reported in this book. Senior undergraduate or graduate students may discover in this book some problems well suited for their own research endeavors.

Author: Bhanu Chander
Publisher: CRC Press
ISBN: 1040027121
Category : Technology & Engineering
Languages : en
Pages : 368

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Book Description
The edited book Intelligent Wireless Sensor Networks and Internet of Things: Algorithms, Methodologies and Applications is intended to discuss the progression of recent as well as future generation technologies for WSNs and IoTs applications through Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). In general, computing time is obviously increased when the massive data is required from sensor nodes in WSN’s. the novel technologies such as 5G and 6G provides enough bandwidth for large data transmissions, however, unbalanced links faces the novel constraints on the geographical topology of the sensor networks. Above and beyond, data transmission congestion and data queue still happen in the WSNs. This book: Addresses the complete functional framework workflow in WSN and IoT domains using AI, ML, and DL models Explores basic and high-level concepts of WSN security, and routing protocols, thus serving as a manual for those in the research field as the beginners to understand both basic and advanced aspects sensors, IoT with ML & DL applications in real-world related technology Based on the latest technologies such as 5G, 6G and covering the major challenges, issues, and advances of protocols, and applications in wireless system Explores intelligent route discovering, identification of research problems and its implications to the real world Explains concepts of IoT communication protocols, intelligent sensors, statistics and exploratory data analytics, computational intelligence, machine learning, and Deep learning algorithms for betterment of the smarter humanity Explores intelligent data processing, deep learning frameworks, and multi-agent systems in IoT-enabled WSN system This book demonstrates and discovers the objectives, goals, challenges, and related solutions in advanced AI, ML, and DL approaches This book is for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Author: Bhanu Chander
Publisher:
ISBN: 9781032764979
Category : Artificial intelligence
Languages : en
Pages : 0

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Book Description
"The edited book Intelligent Wireless Sensor Networks and Internet of Things: Algorithms, Methodologies and Applications is intended to discuss the progression of recent as well as future generation technologies for WSNs and IoTs applications through Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). In general, computing time is obviously increased when the massive data is required from sensor nodes in WSN's. The novel technologies such as 5G and 6G provides enough bandwidth for large data transmissions, however, unbalanced links face the novel constraints on the geographical topology of the sensor networks. Above and beyond, data transmission congestion and data queue still happen in the WSNs. This text: Addresses the complete functional framework workflow in WSN and IoT domains using AI, ML, and DL models. Explores basic and high-level concepts of WSN security, and routing protocols, thus serving as a manual for those in the research field as the beginners to understand both basic and advanced aspects sensors, IoT with ML & DL applications in real-world related technology. Based on the latest technologies such as 5G, 6G and covering the major challenges, issues, and advances of protocols, and applications in wireless system. Explores intelligent route discovering, identification of research problems and its implications to the real world. Explains concepts of IoT communication protocols, intelligent sensors, statistics and exploratory data analytics, computational intelligence, machine learning, and Deep learning algorithms for betterment of the smarter humanity. Explores intelligent data processing, deep learning frameworks, and multi-agent systems in IoT-enabled WSN system. This book demonstrates and discovers the objectives, goals, challenges, and related solutions in advanced AI, ML, and DL approaches. This book is for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology"--

Author: R. Kanthavel
Publisher: John Wiley & Sons
ISBN: 1119821274
Category : Computers
Languages : en
Pages : 388

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Book Description
ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field. Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments. Audience Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies.

Author: Dr. Pooja Singh
Publisher: Shineeks Publishers
ISBN: 163278940X
Category : Education
Languages : en
Pages : 130

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Book Description
The current progress in Wireless Sensor Network has taken to various new protocols formed especially for sensor networks in where the energy awareness is a necessary deliberation. Wireless Sensor Network is highly accessible for significant applications namely surveillance of security and environmental monitoring. The researchers all over the world are investigating about the most important parameter of wireless sensor network i.e. Energy. The main emphasis is given over the efficiency of energy as the energy saved by the wireless sensor network is less and the consumption of energy is high and this is the main reason behind the lifetime network depletion at a fast pace. There in the sensor nodes one more challenge is exhibited that is of the limited power capacity, so for the same the battery should be either charged or changed as there are several functions which are to be performed by the energy of the sensor nodes being aggregation, sensing and transmission of data and on board processing. Majorly, the energy is consumed by the wireless data transmission among the nodes and more energy is consumed as compared to the other sensing and processing operations of data. The high energy is consumed because the data is transmitted over a large distance as the nodes are located far from each other. Further, the collision, overhearing and idle listening of the nodes are the major reasons behind the high wastage of energy during the transmission and the communication of data. There are several applications, in which the nodes are disregarded, and thus worsening the failure of nodes and enhancing the problem of high energy consumption. The success of the application is dependent over the network lifetime and the exchange or the recharging of the batteries is costly as well as not feasible. Therefore, the attention of the researchers is seeking towards usage and the consumption of the energy. Further, the development of such energy efficient network should be done which should cover and provide solution for all the above mentioned challenges so that the utility of the wireless sensor networks is enhanced in the applications related to it. The main intention of this study and book is to investigate in detail about the concept “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks”. Significance of the Book: This book convers and discusses about previous studies carried out in the area of data fusion and the crucial issue in energy reduction of the sensor modes during the data fusion. The main objectives of this book a) To analyze the energy aware routing protocol in wireless sensor network; b) To examine the maximum energy consumption for routing process to sustain long life batter power in wireless sensor network.; c) To analyze the routing protocol enhancement by applying data fusion technique; d)To explore the routing protocol enhancement by applying data fusion technique; e)To propose an algorithm to integrate data fusion technique to enhance the consumption of energy. This book study is constrained to wireless sensor networks and limited to data fusion technique. However, this book study evaluates the concept of “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks”. Finally, this book considers a novel network organization scheme, energy-efficient Self organizing Map (K-SOM) Feed forward scheme, to organize sensor nodes into clusters with Data-Fusion. Also, it proposes a Energy aware routing algorithm, called “Artificial Intelligence Based Energy Aware Routing Protocol (AIEARP) for Wireless Sensor Network, for elevating sensor network lifetime. This book also shows the Experimental results for out-performs interims of network lifetime with dead nodes at different iteration and energy conservation with its energy consumption among the cluster heads. The following is an overview of the contents of the chapter, which presented in this Book. Chapter 1: Introduction of the EARP in WSN This chapter provides the vital idea about the research concept “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks” including the research background, problem statement, aims and objectives of the study, research questions, significance of the study and limitations of the research. Chapter 2: Literature Review This chapter examines several works related to the conceptual framework model for “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks”. In addition to these, this research explains in detail about the energy aware routing protocol in wireless sensor network. Apart from these, this research explains about the maximum energy consumption for routing process to sustain long life batter power in wireless sensor network. At last, this literature review chapter discusses about the routing protocol enhancement by applying data fusion technique and the routing protocol enhancement by applying data fusion technique. In addition to these, this research provides framework for “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks”. Chapter 3: Research design This chapter provides an overview about the intelligent energy aware routing protocol using data fusion technique in wireless sensor networks. This chapter explains about the steps to be followed in the developed method. Chapter 4: Result analysis in term of intelligent energy aware protocol This chapter discusses about the analysis of implementation of proposed framework “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks”. Chapter 5: Conclusion & Future enhancement This chapter explains about the summary of findings obtained through the analysis and results section and also gives conclusion to the research “An Intelligent Energy Aware Routing Protocol using Data Fusion Technique in Wireless Sensor Networks” followed by suggestions and recommendations for the future research. Bibliography: This section lists all works of interest, including those mentioned in the text.

Author: Mazin Gilbert
Publisher: CRC Press
ISBN: 1351130145
Category : Computers
Languages : en
Pages : 498

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Book Description
Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization, highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, software engineers, artificial intelligence, and machine learning researchers.

Author: Jiakai Li
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 331

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Book Description
This dissertation research proposes embedding artificial neural networks into wireless sensor networks in parallel and distributed processing framework to implant intelligence for in-network processing, wireless protocol or application support, and infusion of adaptation capabilities. The goal is to develop in-network "intelligent computation" and "adaptation" capability for wireless sensor networks to improve their functionality, utility and survival aspects. The characteristics of wireless sensor networks bring many challenges, such as the ultra large number of sensor nodes, complex dynamics of network operation, changing topology structure, and the most importantly, the limited resources including power, computation, storage, and communication capability. All these require the applications and protocols running on wireless sensor network to be not only energy-efficient, scalable and robust, but also "adapt" to changing environment or context, and application scope and focus among others, and demonstrate intelligent behavior. The expectation from the research endeavor is to introduce computational intelligence capability for the wireless sensor networks to become adaptive to changes within a variety of operational contexts and to exhibit intelligent behavior. The proposed novel approach entails embedding a wireless sensor network with an artificial neural network algorithm while preserving the parallelism and distributed nature of computations associated with the neural network algorithm. The procedure of embedding an artificial neural network, which may be configured for a problem either at wireless protocol or application levels, into the wireless sensor network hardware platform, which is a parallel and distributed processing system that is composed of a network of motes, is defined. This procedure is demonstrated for a case study with a Hopfield neural network and a minimum weakly connected dominating set problem as the model of wireless sensor network backbone or infrastructure. Issues and challenges pertaining to scalability, solution quality, and computational complexity for time and message are addressed through a comprehensive simulation study. Simulation study is performed using the TOSSIM environment for wireless sensor networks with mote counts up to 1000. A comparative performance evaluation is performed. Solution quality, time and message complexity results for other centralized and distributed algorithms for connected dominating set construction as reported in the literature are used. Additionally, in-house simulation of non-distributed version of the proposed model is implemented to serve as a comparison benchmark and link to the studies in the literature. It is determined through the simulation study that the most critical factors that affect both the time complexity and the message complexity are the network size and time interval. The normalized computation time increases somewhat linearly for the most part for increases in the mote count the exception of the time interval value of 0.1 sec. The message complexity also increases with the increase in the mote count. The message complexity is not sensitive to the radio range but very sensitive to the time interval. All other parameters kept constant, the message complexity decreases with the increase in the time interval value on a consistent basis for all mote counts simulated. For smaller values of time interval, the network is more active due to motes waking up and exchanging messages more frequently, which leads to increased message complexity. The solution quality as measured by the size of the weakly connected dominating set by the proposed model is competitive with the performance exhibited by other algorithms reported in literature given all the adverse effects of computation being realized on a wireless sensor network platform. In light of the fact that there is significant opportunity to improve the entire wireless protocol stack for drastically reducing the time and space complexities through more efficient MAC, time synchronization and routing protocols, there is a strong prospect for the proposed architecture to scale up to tens of thousands of motes.