• Fri frakt över 249 kr
  • •
  • Snabba leveranser
  • •
  • Billiga böcker
Kundservice

Du är på sajten för privatpersoner.

Företag, bibliotek eller offentlig verksamhet?

Du handlar på classic.bokus.com, där alla dina funktioner finns intakta.
Till classic.bokus.com
Bokus logotyp. Gå till startsidan.
  • Erbjudanden
  • Nyheter
  • Student
  • Topplistor
  • Barn & ungdom
  • Bokus Play
  • E-böcker
  • Pocketböcker
  • Spel & pussel

10% rabatt på allt med kod NYSTART10 →

Sidfot

Mina sidor

    Hjälp

    • Kundservice
    • Vanliga frågor och svar
    • Frakt och leverans
    • Retur vid ångerrätt
    • Reklamera vara
    • Betalning
    • Köpvillkor
    • Allmänna villkor
    • Information om webbplatsens tillgänglighet

    Om Bokus

    • Om oss
    • Pressrum
    • För studenter
    • För företag
    • För bibliotek och offentlig verksamhet
    • För leverantörer
    • Hållbarhet

    Populärt

    • Aktuella erbjudanden
    • Presentkort
    • Studentlitteratur
    • Nya böcker
    • Topplistor
    • Signerade böcker
    • Engelska böcker

    Inspiration

    • Boktips
    • BookTok
    • Populära bokserier
    • Barnbokskaraktärer
    • Populära författare
    Logotyp för Bokus
    Följ oss på Facebook (extern länk)Följ oss på Instagram (extern länk)Följ oss på YouTube (extern länk)Följ oss på TikTok (extern länk)
    bokus @ CookiesAnpassa cookiesIntegritetspolicyKöpvillkor
    Till Citymail hemsida (extern länk)Till Budbee hemsida (extern länk)Till Postnord hemsida (extern länk)Till Schenker hemsida (extern länk)Till Early Bird hemsida (extern länk)Till Walleys hemsida (extern länk)
    1. Naturvetenskap och teknik
    2. Teknik och industri
    3. Maskinteknik och material

    Autonomous Vehicles, Volume 2

    Smart Vehicles for Communication

    AvRomil Rawat,Purvee Bhardwaj

    Inbunden, Engelska, 2022

    2 072 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    AUTONOMOUS VEHICLES The companion to Autonomous Vehicles Volume 1: Using Machine Intelligence, this second volume in the two-volume set covers intelligent techniques utilized for designing, controlling, and managing vehicular systems based on advanced algorithms of computing like machine learning, artificial intelligence, data analytics, and Internet of Things (IoT) with prediction approaches to avoid accidental damages, security threats, and theft. Besides communicating with other vehicles, self-driving cars connected to a 5G network will also be able to communicate with different infrastructure elements that make up our roads and other transportation and communication systems. Similarly, an unmanned aerial vehicle (UAV), an aircraft without any human pilot, crew, or passengers on board, can operate under remote control by a human operator, as a remotely-piloted aircraft (RPA), or with various degrees of autonomy. These include autopilot assistance and fully autonomous aircraft that have no provision for human intervention. Transportation is a necessary, but often painful process. With fully autonomous driving, passengers will be freed to accomplish their own goals, turning the dead hours of driving into fruitful hours of learning, working, engaging, and relaxing. Similarly, UAVs can perform functions that human-operated aircraft cannot, whether because of the environment or high-risk situations. The purpose of the book is to present the needs, designs, and applications of autonomous vehicles. The topics covered range from mechanical engineering to computer science engineering, both areas playing vital roles in programming, managing, generating alerts, and GPS position, artificial intelligence-based prediction of path and events, as well as other high-tech tools, are covered in this book, as well. Whether for the student, veteran engineer, or another industry professional, this book, and its companion volume, are must-haves for any library.

    Produktinformation

    • Utgivningsdatum:2022-12-19
    • Mått:238 x 158 x 26 mm
    • Vikt:744 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:352
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394152254

    Utforska kategorier

    • Maskinteknik och material inom Naturvetenskap och teknik

    Mer om författaren

    Romil Rawat, PhD, is an assistant professor at Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore. With over 12 years of teaching experience, he has published numerous papers in scholarly journals and conferences. He has also published book chapters and is a board member on two scientific journals. He has received several research grants and has hosted research events, workshops, and training programs. He also has several patents to his credit. Purvee Bhardwaj, PhD, is the Dean of Physical Science at Rabindranath Tagore University Bhopal MP, India. She has published more than 70 papers in scientific and technical journals and one book. She is a lifetime member of multiple scientific societies and has won numerous awards. Upinder Kaur, PhD, is an assistant professor and head of the Department of Computer Science and Engineering at Akal University and has over 12 years of experience in academics and research. Shrikant Telang, is an assistant professor at Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India. With over eight years of teaching and research experience, he has several patents to his credit and has won numerous awards. Mukesh Chouhan, is an assistant professor and head of the department in the Department of Computer Science & Engineering, Government Polytechnic College, Sanawad, MP, India. He has published several research papers in referred journals, conference papers and book chapters. K. Sakthidasan Sankaran, is a professor in the Department of Electronics and Communication Engineering at Hindustan Institute of Technology and Science, India. He is a reviewer and an editorial board member for several scholarly journals, and he has published more than 70 papers. He also has three books to his credit.

    Innehållsförteckning

    • Preface xiii1 A Best Fit Strategic Approach for Sample Selections of a Carrier to Minimizing Quantization Error 1Virendra P. Nikam and Shital S. Dhande1.1 Introduction 11.1.1 Cryptography 21.1.2 Steganography 31.1.3 Watermarking 31.2 Background History 51.3 Literature Survey 61.4 Proposed Methodology 81.4.1 Carrier Selection 81.4.2 Carrier Classification 81.4.3 Searching Best Fit Sample from Class 91.4.4 Updating Result Carrier with Newly Found Best-Fit Sample 101.5 Result Analysis 131.6 Conclusion 151.7 Future Scope 17References 172 A Dual-Polarized Antenna With Circular Parasitic Element for Autonomous Vehicle 19Manish Varun Yadav and Sudeep Baudha2.1 Introduction 192.2 Autonomous-Vehicle Antenna Design and Principle 212.3 Simulated Parameter Study 242.4 Simulated Results 252.5 Conclusion 30References 303 A Smart Vehicle Antenna for Defence and Satellite Communication 33Manish Varun Yadav, Swati Varun Yadav, Sudeep Baudha and Ashish Chittora3.1 Introduction 343.2 Design Principle and Structure 353.3 Stages of Development 373.4 Simulated Parameter Study 383.5 Simulated and Measured Results 403.6 Conclusion 42References 444 Visual Place Recognition for Simultaneous Localization and Mapping 47Konstantinos A. Tsintotas, Loukas Bampis and Antonios Gasteratos4.1 Introduction 474.2 The Structure for a Visual Place Recognition System 494.2.1 Image Processing 504.2.1.1 Global Descriptor Extraction 504.2.1.2 Local Descriptors Extraction 514.2.2 Map 524.2.2.1 Single Image-Based 534.2.2.2 Sequence of Images-Based 544.2.3 Belief Generator 544.2.3.1 Pixel-Wise Similarity 554.2.3.2 Euclidean or Cosine Distance 564.2.3.3 Vote Density 564.2.3.4 Temporal Consistency 574.2.3.5 Geometrical Verification 574.3 Evaluation 584.3.1 Ground Truth 584.3.2 Datasets 594.3.3 Evaluation Metrics 604.4 Paradigms 614.4.1 Sequence of Images-Based Visual Word Histograms 614.4.2 Dynamic Sequence Segmentation 644.4.3 Hierarchical Mapping Through an Incremental Visual Vocabulary 664.4.4 Bag of Tracked Words for Incremental Visual Place Recognition 674.5 Experimental Results 694.6 Future Trends and Conclusion 70References 715 Trust Verification Class (TVCRO) Based Communication for Enhanced of QoS in VANET Environment 81Akanksha Vyas, Nayan Bhale Amar, Pratiksha Aurangabadkar and Yukti Vyas5.1 Introduction 825.2 Related Work 845.3 Theoretical Framework 865.4 TVCRO Procedure 905.5 Simulation Setup 955.6 Results and Discussion 975.7 Conclusion 99References 1006 Effective Congestion Control Mechanism for Smart Vehicles Using Edge Computing in VANET 105Poorva Shukla, Sunita Varma and Ravindra Petel6.1 Introduction 1066.2 Related Study 1096.3 Proposed Algorithm 1166.4 Conclusion 118Appendix 118References 1197 Longitudinally Variant 4W4D Robot Slipagge-Based Path Tracking Control 123Edgar A. Martínez-García, Roman Lavrenov and Evgeni Magid7.1 Introduction 1247.2 Related Work 1257.3 Vehicle Physical Model 1277.4 4W4D Z-Turn Control Law 1327.5 Sensing Models 1377.6 Path-Tracking Control 1397.7 Conclusion 145Acknowledgement 146References 1468 Intelligent Autonomous Electric Car 151Vijay L. Hallappanavar, Chetan M. Bulla and Mahantesh N. Birje8.1 Introduction 1518.2 Related Work 1548.3 Intelligent Autonomous System 1558.3.1 Object Detection 1568.3.1.1 Object Detection Using IR Sensor 1578.3.2 Automatic Cooling 1588.3.3 Speed Control While Raining 1598.3.4 Automatic Charging 1608.3.5 Hardware Requirement 1628.3.6 Software Requirements 1658.4 Results 1658.4.1 Object Detection and Tracking 1658.4.2 Automatic Cooling 1668.4.3 Speed Control While Raining 1678.4.4 Automatic Charging 1678.5 Conclusions 167References 1689 Cluster Optimization Using Metaheuristic JAYA Algorithm for Secure VANETs 173Gurjot Kaur, Deepti Kakkar and Davinder Singh9.1 Introduction 1749.1.1 VANET Architecture 1769.1.2 VANET Topology 1769.1.3 Challenges in VANETs 1799.1.4 Security Issues in VANETs 1809.1.5 Organization of Chapter 1839.2 Literature Review 1839.2.1 Available Security Solutions for VANETs 1839.2.2 On Trust-Based Security Models 1849.2.3 Gaps in Existing Trust Model-Based Security Solutions 1879.2.4 On Clustering in VANETs Using Metaheuristic Techniques 1889.3 Proposed Work 1919.3.1 Overview 1919.3.2 Assumptions 1919.3.3 Constraints 1929.3.4 Proposed Methodology 1929.4 Conclusion 200References 20010 Analysis of Domestic Cars in India for Middle-Income Group Using TOPSIS 207Vibha Aggarwal, Kulwant Singh, Sandeep Gupta, Shipra Bansal, Priyanka Baghla and Navjot Kaur10.1 Introduction 20810.2 Methodology 20910.3 Result and Discussion 21410.4 Conclusion 214References 21411 A Secure Data Authentication-Based Aerial Intelligent Relay Road Side Unit (AIR-RSU) Framework for Intelligent Transportation System Applications 217A. Samson Arun Raj, M. Roshni Thanka, G. Jaspher Wilisie Kathrine and Yogesh Palanichamy11.1 Introduction 21811.1.1 The Need for Data Authentication 21811.1.2 The Objective of the Proposed Model 21911.2 Related Works 21911.3 Application Scenario of The Working Model 22211.4 Working Process 22411.4.1 Network Measurement Subsystem 22511.4.2 Data Authentication Subsystem 22711.4.3 Service Classification Subsystem 22711.5 Experimental Process 23011.6 Conclusion and Future Works 234References 23512 Evaluation of Vulnerabilities in IoT-Based Intelligent Agriculture Systems 237Khongdet Phasinam and Thanwamas Kassanuk12.1 Introduction 23812.1.1 Precision Agriculture 23812.1.2 Internet of Things and Machine Learning for Smart Agriculture and Related Security Concerns 23812.2 Building Blocks of Internet of Things 24112.2.1 Sensors 24212.2.2 Control Unit 24412.2.3 Communication Module 24512.3 Literature Survey 24712.4 Security Issues 24912.4.1 Heterogeneous Devices and Communication 25012.4.2 Integrating Physical Devices 25012.4.3 Constrained Devices 25012.4.4 Large Scale 25012.4.5 Privacy 25012.5 Attacks and Vulnerabilities in Internet of Things Related to Agriculture Field 25112.6 Conclusion 254References 25513 Q Learning Algorithm for Network Resource Management in Vehicular Communication Network 259Vartika Agarwal and Sachin Sharma13.1 Introduction 25913.2 Literature Review 26113.3 Overview of Network Resource Management in Vehicular Communication Networks 26313.4 Reinforcement Learning Techniques for Network Resource Management 26413.5 Applications of Q Learning 26613.6 Comparative Study and Result Analysis 26813.7 Impact of Q-Learning 27113.8 Conclusion 271References 27214 Reliable Transportation Solution for Urban Planning: VANET 275Harshit Srivastava and Deepti Kakkar14.1 Introduction 27614.1.1 VANET Architecture 27614.1.2 VANET Characteristics 27814.1.3 VANET Standards 27814.1.4 VANET Communication 27914.1.5 Implementation of Optimisation Algorithm for VANETs 27914.2 Cryptography 28214.2.1 Salient Features of Cryptography 28214.2.2 Classification of Cryptography (as shown in Figure 14.2) 28314.3 Common Security Attacks 28314.4 Gaps in Present Cryptography 28414.5 Lightweight Cryptography 28514.5.1 Vital Security Aspects in Lightweight Cryptography 28614.5.2 Advantages of Lightweight Protocols 28714.5.3 Objectives of Lightweight Protocols are Classified as 28814.5.4 Lightweight Cryptography Algorithms 28914.5.5 Software and Hardware Implementation 29014.5.5.1 Hardware Lightweight Cryptography 29014.5.5.2 Software Lightweight Cryptography 29114.5.6 Division of Lightweight Cryptography 29114.5.6.1 Symmetric Key Algorithm 29214.5.6.2 Asymmetric Key 29714.6 Conclusion 29914.7 Future Work 300References 30015 Implementation of Veco-Taxis in Turbulent Environment for Gas Source Localization 303Kumar Gaurav15.1 Introduction 30315.2 Literature Survey 30415.3 Methodology 30715.4 Results and Discussions 31015.5 Conclusions 314References 31516 A Technique for Monitoring Cyber-Attacks on Self-Driving Automobiles-Based VANET 317Vinod Mahor, Sadhna Bijrothiya, Rina Mishra and Romil Rawat16.1 Introduction 31816.2 Related Work 31916.3 Examining the Proposed Framework 32016.4 Conclusion 331References 331About the Editors 335Index 337