This book provides a comprehensive analysis of Brooks-Iyengar Distributed Sensing Algorithm, which brings together the power of Byzantine Agreement and sensor fusion in building a fault-tolerant distributed sensor network. The authors analyze its long-term impacts, advances, and future prospects. The book starts by discussing the Brooks-Iyengar algorithm, which has made significant impact since its initial publication in 1996. The authors show how the technique has been applied in many domains such as software reliability, distributed systems and OS development, etc. The book exemplifies how the algorithm has enhanced new real-time features by adding fault-tolerant capabilities for many applications. The authors posit that the Brooks-Iyengar Algorithm will to continue to be used where fault-tolerant solutions are needed in redundancy system scenarios. This book celebrates S.S. Iyengar's accomplishments that led to his 2019 Institute of Electrical and Electronics Engineers' (IEEE) Cybermatics Congress "Test of Time Award" for his work on creating Brooks-Iyengar Algorithm and its impact in advancing modern computing.

The vision of researchers to create smart environments through the deployment of thousands of sensors, each with a short range wireless communications channel and capable of detecting ambient conditions such as temperature, movement, sound, light, or the presence of certain objects is becoming a reality. With the emergence of high-speed networks an

The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for students or as research material for engineers, the book gives readers up-to-date, practical insight on all aspects of the field. Revised and expanded, this second edition incorporates contributions from many veterans of the DARPA ISO SENSIT program as well as new material from distinguished researchers in the field. Sensor Networking and Applications focuses on sensor deployment and networking, adaptive tasking, self-configuration, and system control. In the expanded applications section, the book draws on the insight of practitioners in the field. Readers of this book may also be interested in Distributed Sensor Networks, Second Edition: Image and Sensor Signal Processing (ISBN: 9781439862827).

This is the only book to cover infrastructure aspects of sensor networks in a comprehensive fashion. The only other books on sensor networks do not cover this topic or do so only superficially as part of a less-focussed multi-authored treatment.

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.

This book provides a Mathematical Theory of Distributed Sensor Networks. It introduces the Mathematical & Computational Structure by discussing what they are, their applications and how they differ from traditional systems. It also explains how mathematics are utilized to provide efficient techniques implementing effective coverage, deployment, transmission, data processing, signal processing, and data protection within distributed sensor networks. Finally, it discusses some important challenges facing mathematics to get more incite to the multidisciplinary area of distributed sensor networks. -This book will help design engineers to set up WSN-based applications providing better use of resources while optimizing processing costs. -This book is highly useful for graduate students starting their first steps in research to apprehend new approaches and understand the mathematics behind them and face promising challenges. -This book aims at presenting a formal framework allowing to show how mathematical theories can be used to provide distributed sensor modeling and to solve important problems such as coverage hole detection and repair. -This book aims at presenting the current state of the art in formal issues related to sensor networking. It can be used as a handbook for different classes at the graduate level and the undergraduate level. It is self contained and comprehensive, presenting a complete picture of the discipline of optical network engineering including modeling functions, controlling quality of service, allocation resources, monitoring traffic, protecting infrastructure, and conducting planning. This book addresses a large set of theoretical aspects. It is designed for specialists in ad hoc and wireless sensor networks and does not include discusses on very promising areas such as homotopy, computational geometry, and wavelet transforms.

This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems.

The use of Unmanned Aerial Vehicles (UAVs) or ‘drones’ continues to increase, and keeping up to date with technological, legal and commercial developments related to this domain is important, particularly with regard to safety and security in regional and border security operations. This book presents edited contributions from the NATO Advanced Training Course (ATC) entitled “Modern technologies enabling safe and secure UAV operation in urban airspace”, held in Agadir, Morocco, from 25 to 30 November 2019. Participants included experienced scientists and industry engineers involved in UAV development and activity, and the aim of the ATC was to increase awareness among all NATO and partner countries of the safety and security challenges raised by UAV flights in urban airspace, as well as sharing the knowledge and expertise of specialists working to advance the technologies and capabilities that will enhance safety and security across NATO and its partner countries. The ATC began with a presentation about current UAV technologies, and the technological features that might present a threat to the safety of commercial or military airspace applications. Other topics covered included the U-space concept; management of UAV operations in controlled airspace; integration of manned and unmanned aviation; testing and certification of UAVs; autonomous UAV flights; application of UAVs in urban airspace; and BVLOS flights and sensors for UAV navigation and communication. The book will be of interest to all those working with UAVs or seeking to develop and encourage their use, particularly for security purposes.

Natural computing brings together nature and computing to develop new computational tools for problem solving; to synthesize natural patterns and behaviors in computers; and to potentially design novel types of computers. Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications presents a wide-ranging survey of novel techniqu

This book provides the basics needed to develop sensor network software and supplements it with many case studies covering network applications. It also examines how to develop onboard applications on individual sensors, how to interconnect these sensors, and how to form networks of sensors, although the major aim of this book is to provide foundational principles of developing sensor networking software and critically examine sensor network applications.