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Author: Itshak Tkach
Publisher: Springer Nature
ISBN: 3030347354
Category : Technology & Engineering
Languages : en
Pages : 145
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Book Description
Today’s real-world problems and applications in sensory systems and target detection require efficient, comprehensive and fault-tolerant multi-sensor allocation. This book presents the theory and applications of novel methods developed for such sophisticated systems. It discusses the advances in multi-agent systems and AI along with collaborative control theory and tools. Further, it examines the formulation and development of an allocation framework for heterogeneous multi-sensor systems for various real-world problems that require sensors with different performances to allocate multiple tasks, with unknown a priori priorities that arrive at unknown locations at unknown time. It demonstrates how to decide which sensor to allocate to which tasks when and where. Lastly, it explains the reliability and availability issues of task allocation systems, and includes methods for their optimization. The presented methods are explained, measured, and evaluated by extensive simulations, and the results of these simulations are presented in this book. This book is an ideal resource for academics, researchers and graduate students as well as engineers and professionals and is relevant for various applications such as sensor network design, multi-agent systems, task allocation, target detection, and team formation.
Author: Itshak Tkach
Publisher: Springer Nature
ISBN: 3030347354
Category : Technology & Engineering
Languages : en
Pages : 145
Get Book Here
Book Description
Today’s real-world problems and applications in sensory systems and target detection require efficient, comprehensive and fault-tolerant multi-sensor allocation. This book presents the theory and applications of novel methods developed for such sophisticated systems. It discusses the advances in multi-agent systems and AI along with collaborative control theory and tools. Further, it examines the formulation and development of an allocation framework for heterogeneous multi-sensor systems for various real-world problems that require sensors with different performances to allocate multiple tasks, with unknown a priori priorities that arrive at unknown locations at unknown time. It demonstrates how to decide which sensor to allocate to which tasks when and where. Lastly, it explains the reliability and availability issues of task allocation systems, and includes methods for their optimization. The presented methods are explained, measured, and evaluated by extensive simulations, and the results of these simulations are presented in this book. This book is an ideal resource for academics, researchers and graduate students as well as engineers and professionals and is relevant for various applications such as sensor network design, multi-agent systems, task allocation, target detection, and team formation.
Author: Diego Pizzocaro
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
A sensor network often consists of a large number of sensing devices of different types. Upon deployment in the field, these sensing devices form an ad hoc network using wireless links or cables to communicate with each other. Sensor networks are increasingly used to support emergency responders in the field usually requiring many sensing tasks to be supported at the same time. By a sensing task we mean any job that requires some amount of sensing resources to be accomplished such as localizing persons in need of help or detecting an event. Tasks might share the usage of a sensor, but more often compete to exclusively control it because of the limited number of sensors and overlapping needs with other tasks. Sensors are in fact scarce and in high demand. In such cases, it might not be possible to satisfy the requirements of all tasks using available sensors. Therefore, the fundamental question to answer is: "Which sensor should be allocated to which task?", which summarizes the Multi-Sensor Task Allocation (MSTA) problem. We focus on a particular MSTA instance where the environment does not provide enough information to plan for future allocations constraining us to perform instantaneous allocation. We look at this problem in both static setting, where all task requests from emergency responders arrive at once, and dynamic setting, where tasks arrive and depart over time. We provide novel solutions based on centralized and distributed approaches. We evaluate their performance using mainly simulations on randomly generated problem instances; moreover, for the dynamic setting, we consider also feasibility of deploying part of the distributed allocation system on user mobile devices. Our solutions scale well with different number of task requests and manage to improve the utility of the network, prioritizing the most important tasks.
Author: Victor Lesser
Publisher: Springer Science & Business Media
ISBN: 1461503639
Category : Computers
Languages : en
Pages : 377
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Book Description
Distributed Sensor Networks is the first book of its kind to examine solutions to this problem using ideas taken from the field of multiagent systems. The field of multiagent systems has itself seen an exponential growth in the past decade, and has developed a variety of techniques for distributed resource allocation. Distributed Sensor Networks contains contributions from leading, international researchers describing a variety of approaches to this problem based on examples of implemented systems taken from a common distributed sensor network application; each approach is motivated, demonstrated and tested by way of a common challenge problem. The book focuses on both practical systems and their theoretical analysis, and is divided into three parts: the first part describes the common sensor network challenge problem; the second part explains the different technical approaches to the common challenge problem; and the third part provides results on the formal analysis of a number of approaches taken to address the challenge problem.
Author: Anis Koubâa
Publisher: Springer
ISBN: 3319182994
Category : Technology & Engineering
Languages : en
Pages : 274
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Book Description
This book compiles some of the latest research in cooperation between robots and sensor networks. Structured in twelve chapters, this book addresses fundamental, theoretical, implementation and experimentation issues. The chapters are organized into four parts namely multi-robots systems, data fusion and localization, security and dependability, and mobility.
Author: Sagayam, K. Martin
Publisher: IGI Global
ISBN: 1799850692
Category : Computers
Languages : en
Pages : 405
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Book Description
Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to their resource-constrained nature, which is why researchers have begun applying several branches of artificial intelligence to advance the security of these networks. Research is needed on the development of security practices in wireless sensor networks by using smart technologies. Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks provides emerging research exploring the theoretical and practical advancements of security protocols in wireless sensor networks using artificial intelligence-based techniques. Featuring coverage on a broad range of topics such as clustering protocols, intrusion detection, and energy harvesting, this book is ideally designed for researchers, developers, IT professionals, educators, policymakers, practitioners, scientists, theorists, engineers, academicians, and students seeking current research on integrating intelligent techniques into sensor networks for more reliable security practices.
Author: Hanjiao Qiu
Publisher:
ISBN:
Category : Multisensor data fusion
Languages : en
Pages : 58
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Book Description
The current U.S. transportation infrastructures require tremendous investments to maintain due to critical roadway and pavement conditions. To prioritize the repair expenditures, Cyber-Physical Systems (CPS) are a promising solution to obtain intrinsic knowledge about infrastructure performance such as roadway surface and subsurface deterioration through sensors and actuators. However, to characterize and quantify the infrastructures' time varying behavior (infrastructure health and life cycle) in a cost-efficient and non-intrusive way, an underlying framework to handle domain-specific big data in CPS is needed. This paper proposes a holistic approach to manage domain-specific bulk sensor data generated from heterogeneous distributed sensor systems to address CPS meeting big data. We focused on the big data handling in a Scalable Intelligent ROaming Multi-Modal Multi-Sensor (SIROM3) framework, which collects data about roadway conditions from multiple domains through mobile agents. A Heterogeneous Stream File-system Overlay (HSFO) is proposed as a platform-independent layer to uniformly define, organize and manage the high volume of heterogeneous streaming data. Additionally, a flexible plugin system (PLEX) is introduced to simplify and automate data feature extraction, correlation, fusion and visualization. Both HSFO and PLEX are designed with high scalability and adaptability. They can be executed on a wide range of platforms from mobile systems to mainstream servers with a common software/hardware stack. Our solution addresses big data collection, storage, aggregation to processing and knowledge discovery. The embodied automation eliminates human intervention at every stage and increases overall efficiency. Over 20 terabytes of data covering 300 miles have been collected, aggregated, and fused for comprehending the pavement dynamics of the entire city of Brockton, MA. The performance of data processing with and without HSFO was compared. The results indicate that processing data with HSFO takes an overhead of 0.19 μs/KB than that in the absence of HSFO. The difference of CPU utilization between two methods is less than 5%. This implies that HSFO and PLEX has quite low overhead with a negligible impediment to the system performance. The unified automation fulfilled by them has demonstrated a significant increase in overall productivity by nearly 25 times, starting from data collection to processing. In result, we established foundational tools for managing the big data for distributed multi-modal multi-sensor systems in civil infrastructure monitoring. They provide rapid and comprehensive understanding of civil infrastructure health and life cycle management.
Author: Anibal Ollero
Publisher: Springer
ISBN: 3319708333
Category : Technology & Engineering
Languages : en
Pages : 913
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Book Description
These volumes of "Advances in Intelligent Systems and Computing" highlight papers presented at the "Third Iberian Robotics Conference (ROBOT 2017)". Held from 22 to 24 November 2017 in Seville, Spain, the conference is a part of a series of conferences co-organized by SEIDROB (Spanish Society for Research and Development in Robotics) and SPR (Portuguese Society for Robotics). The conference is focused on Robotics scientific and technological activities in the Iberian Peninsula, although open to research and delegates from other countries. Thus, it has more than 500 authors from 21 countries. The volumes present scientific advances but also robotic industrial applications, looking to promote new collaborations between industry and academia.
Author: Albert Y. Zomaya
Publisher: John Wiley & Sons
ISBN: 1118342003
Category : Computers
Languages : en
Pages : 605
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Book Description
The energy consumption issue in distributed computing systems raises various monetary, environmental and system performance concerns. Electricity consumption in the US doubled from 2000 to 2005. From a financial and environmental standpoint, reducing the consumption of electricity is important, yet these reforms must not lead to performance degradation of the computing systems. These contradicting constraints create a suite of complex problems that need to be resolved in order to lead to 'greener' distributed computing systems. This book brings together a group of outstanding researchers that investigate the different facets of green and energy efficient distributed computing. Key features: One of the first books of its kind Features latest research findings on emerging topics by well-known scientists Valuable research for grad students, postdocs, and researchers Research will greatly feed into other technologies and application domains
Author: Chin-Yin Huang
Publisher: Springer Nature
ISBN: 303144373X
Category : Technology & Engineering
Languages : en
Pages : 500
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Book Description
This book is a groundbreaking exploration of the historical and contemporary challenges in systems collaboration and integration. This exceptional book delves into engineering design, planning, control, and management, offering invaluable insights into the evolving nature of systems and networks. In an era defined by the ongoing cyber and digital transformation, coupled with artificial intelligence and machine learning, this book offers insights into the future of systems collaboration and integration. Over the past three decades, the PRISM Center and its affiliated PRISM Global Research Network (PGRN) have spearheaded pioneering theories, technologies, and applications in the realm of systems collaboration and integration. Their research, driven by the motto “Knowledge through information; Wisdom through collaboration,” has yielded remarkable advancements. Those achievements and papers presented and updated by the PGRN scholars in the 26th ICPR are included in this book.
Author: Ying Tan
Publisher: Springer
ISBN: 3642309763
Category : Computers
Languages : en
Pages : 646
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Book Description
This book and its companion volume, LNCS vols. 7331 and 7332, constitute the proceedings of the Third International Conference on Swarm Intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The 145 revised full papers presented were carefully reviewed and selected from 247 submissions. The papers are organized in 27 cohesive sections covering all major topics of swarm intelligence research and developments.
