Download or read book Applications of Machine Learning in UAV Networks written by Hassan, Jahan and published by IGI Global. This book was released on 2024-01-17 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy. This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond.
Download or read book Deep Learning for Unmanned Systems written by Anis Koubaa and published by Springer Nature. This book was released on 2021-10-01 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.
Download or read book Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques written by Thusnavis, Bella Mary I. and published by IGI Global. This book was released on 2022-05-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicles (UAVs) and artificial intelligence (AI) are gaining the attention of academic and industrial researchers due to the freedoms that UAVs afford when operating and monitoring activities remotely. Applying machine learning and deep learning techniques can result in fast and reliable outputs and have helped in real-time monitoring, data collection and processing, and prediction. UAVs utilizing these techniques can become instrumental tools for computer/wireless networks, smart cities, military applications, agricultural sectors, and mining. Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques is an essential reference source that covers pattern recognition, machine and deep learning-based methods, and other AI techniques and the impact they have when applied to different real-time applications of UAVs. It synthesizes the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems, and numerous application areas. Covering topics such as vehicular surveillance systems, yield prediction, and human activity recognition, this premier reference source is a comprehensive resource for computer scientists; AI engineers; data scientists; agriculturalists; government officials; military leaders; business managers and leaders; students and faculty of higher education; academic libraries; academicians; and researchers in computer science, computer vision, pattern recognition, imaging, and engineering.
Download or read book The Internet of Drones written by Arun Solanki and published by CRC Press. This book was released on 2022-11-03 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, drones have been integrated with the Internet of Things to offer a variety of exciting new applications. Here is a detailed exploration of adapting and implementing Internet of Drones technologies in real-world applications, emphasizing solutions to architectural challenges and providing a clear overview of standardization and regulation, implementation plans, and privacy concerns. The book discusses the architectures and protocols for drone communications, implementing and deploying of 5G-drone setups, security issues, deep learning techniques applied on real-time footage, and more. It also explores some of the varied applications, such as for monitoring and analysis of troposphere pollutants, providing services and communications in smart cities (such as for weather forecasting, communications, transport, safety and protection), for disaster relief management, for agricultural crop monitoring, and more.
Download or read book Handbook of Research on Machine and Deep Learning Applications for Cyber Security written by Ganapathi, Padmavathi and published by IGI Global. This book was released on 2019-07-26 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Download or read book Drone Technology written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2023-06-20 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: DRONE TECHNOLOGY This book provides a holistic and valuable insight into the revolutionary world of unmanned aerial vehicles (UAV). The book elucidates the revolutionary and riveting research in the ultramodern domain of drone technologies, drone-enabled IoT applications, and artificial intelligence-based smart surveillance. The book explains the most recent developments in the field, challenges, and future scope of drone technologies. Beyond that, it discusses the importance of a wide range of design applications, drone/UAV development, and drone-enabled smart healthcare systems for smart cities. It describes pioneering work on mitigating cyber security threats by employing intelligent machine learning models in the designing of IoT-aided drones. The book also has a fascinating chapter on application intrusion detection by drones using recurrent neural networks. Other chapters address interdisciplinary fields like artificial intelligence, deep learning, the role of drones in healthcare in smart cities, and the importance of drone technology in agriculture. Audience The book will be read and consulted by a range of industry engineers involved with introducing drone technology to their daily operations.
Download or read book Machine Learning for Complex and Unmanned Systems written by Jose Martinez-Carranza and published by CRC Press. This book was released on 2024-02-21 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of artificial intelligence, cryptography, embedded hardware, electronics, the Internet of Things, and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research. Features Provides details of applications using machine learning methods to solve real problems in engineering Discusses new developments in the areas of complex and unmanned systems Includes details of hardware/software implementation of machine learning methods Includes examples of applications of different machine learning methods for future lines for research in the hot topic areas of submarines, drones, robots, cryptography, electronics, healthcare, and the Internet of Things This book can be used by graduate students, industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling, simulation, and optimization of complex systems, cryptography, electronics, healthcare, control systems, Internet of Things, security, and unmanned systems such as submarines, drones, and robots.
Download or read book Artificial Intelligence Machine Learning and Blockchain in Quantum Satellite Drone and Network written by Thiruselvan Subramanian and published by CRC Press. This book was released on 2022-10-14 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum computing is a field in which advanced technologies like quantum communication, artificial intelligence and machine learning can be used to secure and speed up connectivity using quantum computers, quantum drones or quantum satellites. This book serve as a foundation for researchers and scientists in this field. Future technologies, such as quantum drone delivery systems, quicker internet and climate change mitigation, will need quantum information processing and quantum computation. This book deeply explores the importance of quantum computing in real-time applications. It may be used as a reference book for students in higher education, including undergraduate and graduate students, as well as researchers. Key features: Provides a clear insight into the Internet of Drones for academicians, postdoc fellows, research scholars, graduate and postgraduate students, industry fellows and software engineers Useful to professionals who seek information about the Internet of Drones, including experts in quantum computing and physics and post-quantum cryptography, as well as data scientists and data analysts Covers quantum computing and security for Unmanned Aerial Vehicles (UAV) or drones which are widely useful for applications such as military, government, and non-government systems Explores futuristic aspects of the Intenet of Drones to improve everyday living for ordinary people
Download or read book Engineering Applications of Neural Networks written by John Macintyre and published by Springer. This book was released on 2019-05-14 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.
Download or read book Drones in Smart Cities written by Fadi Al-Turjman and published by Elsevier. This book was released on 2020-06-04 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drones in Smart-Cities: Security and Performance is the first book dedicated to drones in smart cities, helping address the many research challenges in bringing UAVs into practice. The book incorporates insights from the latest research in Internet of Things, big data, and cloud computing, 5G, and other communication technologies. It examines the design and implementation of UAV, focusing on data delivery, performability, and security. Intended for researchers, engineers, and practitioners, Drones in Smart-Cities: Security and Performance combines the technical aspects with academic theory to help implement the smart city vision around the globe. Addresses UAV and IoT for smart cities applications Examines topics as UAV safety, challenges, localization methods. QoS, simulation tools, and more Collect the relevant knowledge in one resource, saving research time and effort
Download or read book Computational Intelligence for Unmanned Aerial Vehicles Communication Networks written by Mariya Ouaissa and published by Springer Nature. This book was released on 2022-03-29 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide a vision that can combine the best of both Artificial Intelligence (AI) and communication networks for designing the deployment trajectory to establish flexible Unmanned Aerial Vehicles (UAV) communication networks.This book will discuss the major challenges that can face deploying unmanned aerial vehicles in emergent networks. It will focus on possible applications of UAV in a Smart City environment where they can be supported by Internet of Things (IoT), wireless sensor networks, as well as 5G, and beyond. This book presents the possible problems and solutions, the network integration of the UAV and compare the communication technologies to be used.This book will be a collection of original contributions regarding state of the art AI/ML based solutions in UAV communication networks which can be used for routing protocol design, transport layer optimization, user/application behaviour prediction, communication network optimization, security, and anomaly detection.
Download or read book UAV or Drones for Remote Sensing Applications written by Felipe Gonzalez Toro and published by MDPI. This book was released on 2018-11-23 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "UAV or Drones for Remote Sensing Applications" that was published in Sensors
Download or read book Drone Data Analytics in Aerial Computing written by P. Karthikeyan and published by Springer Nature. This book was released on 2023-09-26 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the latest research, theoretical, and experimental research innovations in drone data analytics in aerial computing. Drone data analytics guarantees that the right people have the correct data at their fingertips whenever they need it. The contents also discuss the challenges faced with drone data analytics, such as due to the high mobility of drones, aerial computing is significantly different from terrestrial computing. It also includes case studies from leading drone vendors. The book also focuses on the comparison of data management and security mechanisms in drone data analytics. This book is useful to those working in agriculture, mining, waste management, and defenses department.
Download or read book Unmanned Aerial Vehicles in Smart Cities written by Fadi Al-Turjman and published by Springer. This book was released on 2020-05-19 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the major challenges in realizing unmanned aerial vehicles (UAVs) in IoT-based Smart Cities. The challenges tackled vary from cost and energy efficiency to availability and service quality. The aim of this book is to focus on both the design and implementation aspects of the UAV-based approaches in IoT-enabled smart cities’ applications that are enabled and supported by wireless sensor networks, 5G, and beyond. The contributors mainly focus on data delivery approaches and their performability aspects. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies. Involves the most up to date unmanned aerial vehicles (UAV) assessment and evaluation approaches Includes innovative operational ideas in agriculture, surveillance, rescue, etc. Pertains researchers, scientists, engineers and practitioners in the field of smart cities, IoT, and communications Fadi Al-Turjman received his Ph.D. from Queen’s University, Canada. He is a full professor and a research center director at Near East University, Nicosia. He is a leading authority in the area of IoT and intelligent systems. His publication history spans over 250 publications inaddition to his editorialship in top journals such as the IEEE Communication Surveys and Tutorials, and the Elsevier Sustaibable Cities and Sociaty.
Download or read book Applications of Computer Vision and Drone Technology in Agriculture 4 0 written by Siddharth Singh Chouhan and published by Springer Nature. This book was released on with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Learning and Its Applications for Vehicle Networks written by Fei Hu and published by CRC Press. This book was released on 2023-05-12 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.
Download or read book TinyML for Edge Intelligence in IoT and LPWAN Networks written by Bharat S Chaudhari and published by Elsevier. This book was released on 2024-06-17 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to IoT and LPWANs. It starts by providing the foundations of IoT/LPWANs, low power embedded systems and hardware, the role of artificial intelligence and machine learning in communication networks in general and cloud/edge intelligence. It then presents the concepts, methods, algorithms and tools of TinyML. Practical applications of the use of TinyML are given from health and industrial fields which provide practical guidance on the design of applications and the selection of appropriate technologies. TinyML for Edge Intelligence in IoT and LPWAN Networks is highly suitable for academic researchers and professional system engineers, architects, designers, testers, deployment engineers seeking to design ultra-lower power and time-critical applications. It would also help in designing the networks for emerging and future applications for resource-constrained nodes. This book provides one-stop solutions for emerging TinyML for IoT and LPWAN applications. The principles and methods of TinyML are explained, with a focus on how it can be used for IoT, LPWANs, and 5G applications. Applications from the healthcare and industrial sectors are presented. Guidance on the design of applications and the selection of appropriate technologies is provided.