Adaptive Sampling with Mobile WSN

Adaptive Sampling with Mobile WSN PDF Author: Koushil Sreenath
Publisher:
ISBN: 9780542466519
Category : Electrical engineering and electronics
Languages : en
Pages :

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Book Description
The spatiotemporally varying network topology of mobile sensor networks makes it very suitable for applications such as reconstruction of environmental fields through sampling at locations that maximally reduce the largest uncertainty in the field estimate. Mobile sensor networks comprise of multiple heterogeneous resources and a deadlock-free resource scheduling in the presence of shared and routing resources becomes necessary to schedule the most efficient (cost/energy/time) resource for a task. Location information is imperative in sensor networks for most applications for localized sensing where localizing the network adaptively with no additional hardware is important. Adaptive sampling approaches for spatially distributed static linear and Gaussian fields with mobile robotic sensors are formulated and experimentally validated. Resource scheduling algorithms for dispatching resources in a deadlock-free manner in systems with shared and routing resources are mathematically formulated and experimentally validated. Simultaneous and Adaptive localization algorithms for sensor network localization through simple geometric constraints are validated through simulations. (Abstract shortened by UMI.).

Adaptive Sampling with Mobile WSN

Adaptive Sampling with Mobile WSN PDF Author: Koushil Sreenath
Publisher:
ISBN: 9780542466519
Category : Electrical engineering and electronics
Languages : en
Pages :

Get Book

Book Description
The spatiotemporally varying network topology of mobile sensor networks makes it very suitable for applications such as reconstruction of environmental fields through sampling at locations that maximally reduce the largest uncertainty in the field estimate. Mobile sensor networks comprise of multiple heterogeneous resources and a deadlock-free resource scheduling in the presence of shared and routing resources becomes necessary to schedule the most efficient (cost/energy/time) resource for a task. Location information is imperative in sensor networks for most applications for localized sensing where localizing the network adaptively with no additional hardware is important. Adaptive sampling approaches for spatially distributed static linear and Gaussian fields with mobile robotic sensors are formulated and experimentally validated. Resource scheduling algorithms for dispatching resources in a deadlock-free manner in systems with shared and routing resources are mathematically formulated and experimentally validated. Simultaneous and Adaptive localization algorithms for sensor network localization through simple geometric constraints are validated through simulations. (Abstract shortened by UMI.).

Adaptive Sampling with Mobile WSN

Adaptive Sampling with Mobile WSN PDF Author: Koushil Sreenath
Publisher: Institution of Engineering and Technology
ISBN: 9781849192576
Category : Technology & Engineering
Languages : en
Pages : 0

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Book Description
Adaptive Sampling with Mobile WSN develops algorithms for optimal estimation of environmental parametric fields. With a single mobile sensor, several approaches are presented to solve the problem of where to sample next to maximally and simultaneously reduce uncertainty in the field estimate and uncertainty in the localisation of the mobile sensor while respecting the dynamics of the time-varying field and the mobile sensor. A case study of mapping a forest fire is presented. Multiple static and mobile sensors are considered next, and distributed algorithms for adaptive sampling are developed resulting in the Distributed Federated Kalman Filter. However, with multiple resources a possibility of deadlock arises and a matrix-based discrete-event controller is used to implement a deadlock avoidance policy. Deadlock prevention in the presence of shared and routing resources is also considered. Finally, a simultaneous and adaptive localisation strategy is developed to simultaneously localise static and mobile sensors in the WSN in an adaptive manner. Experimental validation of several of these algorithms is discussed throughout the book.

Adaptive Sampling with Mobile WSN

Adaptive Sampling with Mobile WSN PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Wireless Sensor Networks and Applications

Wireless Sensor Networks and Applications PDF Author: Yingshu Li
Publisher: Springer Science & Business Media
ISBN: 0387495924
Category : Computers
Languages : en
Pages : 444

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Book Description
A crucial reference tool for the increasing number of scientists who depend upon sensor networks in a widening variety of ways. Coverage includes network design and modeling, network management, data management, security and applications. The topic covered in each chapter receives expository as well as scholarly treatment, covering its history, reviewing state-of-the-art thinking relative to the topic, and discussing currently unsolved problems of special interest.

Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks

Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks PDF Author: Yunfei Xu
Publisher: Springer
ISBN: 3319219219
Category : Technology & Engineering
Languages : en
Pages : 115

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Book Description
This brief introduces a class of problems and models for the prediction of the scalar field of interest from noisy observations collected by mobile sensor networks. It also introduces the problem of optimal coordination of robotic sensors to maximize the prediction quality subject to communication and mobility constraints either in a centralized or distributed manner. To solve such problems, fully Bayesian approaches are adopted, allowing various sources of uncertainties to be integrated into an inferential framework effectively capturing all aspects of variability involved. The fully Bayesian approach also allows the most appropriate values for additional model parameters to be selected automatically by data, and the optimal inference and prediction for the underlying scalar field to be achieved. In particular, spatio-temporal Gaussian process regression is formulated for robotic sensors to fuse multifactorial effects of observations, measurement noise, and prior distributions for obtaining the predictive distribution of a scalar environmental field of interest. New techniques are introduced to avoid computationally prohibitive Markov chain Monte Carlo methods for resource-constrained mobile sensors. Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks starts with a simple spatio-temporal model and increases the level of model flexibility and uncertainty step by step, simultaneously solving increasingly complicated problems and coping with increasing complexity, until it ends with fully Bayesian approaches that take into account a broad spectrum of uncertainties in observations, model parameters, and constraints in mobile sensor networks. The book is timely, being very useful for many researchers in control, robotics, computer science and statistics trying to tackle a variety of tasks such as environmental monitoring and adaptive sampling, surveillance, exploration, and plume tracking which are of increasing currency. Problems are solved creatively by seamless combination of theories and concepts from Bayesian statistics, mobile sensor networks, optimal experiment design, and distributed computation.

Emerging Technologies in Wireless Ad-hoc Networks: Applications and Future Development

Emerging Technologies in Wireless Ad-hoc Networks: Applications and Future Development PDF Author: Aquino-Santos, Raul
Publisher: IGI Global
ISBN: 1609600290
Category : Computers
Languages : en
Pages : 419

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Book Description
Mobile ad-hoc networks have attracted considerable attention and interest from the commercial sector as well as the standards community. Many new ad-hoc networking applications have been conceived to help enable new commercial and personal communication beyond the domain of tactical networks, including personal area networking, home networking, law enforcement operations, search and rescue operations, commercial and educational applications, and sensor networks. Emerging Technologies in Wireless Ad-hoc Networks: Applications and Future Development provides the rationale, state-of-the-art studies and practical applications, proof-of-concepts, experimental studies, and future development on the use of emerging technologies in wireless ad-hoc networks. In addition, this work explores emerging wireless ad hoc technologies based on communication coverage areas: body sensor networks, personal area networks, local area networks, and metropolitan area networks and their applications in critical sectors, for example, agriculture, environment, public health and public transportation.

Wireless Sensor Networks

Wireless Sensor Networks PDF Author: Ibrahiem M. M. El Emary
Publisher: CRC Press
ISBN: 1466518103
Category : Computers
Languages : en
Pages : 804

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Book Description
Although there are many books available on WSNs, most are low-level, introductory books. The few available for advanced readers fail to convey the breadth of knowledge required for those aiming to develop next-generation solutions for WSNs. Filling this void, Wireless Sensor Networks: From Theory to Applications supplies comprehensive coverage of WSNs. In order to provide the wide-ranging guidance required, the book brings together the contributions of domain experts working in the various subfields of WSNs worldwide. This edited volume examines recent advances in WSN technologies and considers the theoretical problems in WSN, including issues with monitoring, routing, and power control. It also details methodologies that can provide solutions to these problems. The book’s 25 chapters are divided into seven parts: Data Collection Physical Layer and Interfacing Routing and Transport Protocols Energy-Saving Approaches Mobile and Multimedia WSN Data Storage and Monitoring Applications The book examines applications of WSN across a range of fields, including health, military, transportation, and mining. Addressing the main challenges in applying WSNs across all phases of our life, it explains how WSNs can assist in community development. Complete with a list of references at the end of each chapter, this book is ideal for senior undergraduate and postgraduate students, researchers, scholars, academics, industrial researchers, and practicing engineers working on WSNs. The text assumes that readers possess a foundation in computer networks, wireless communication, and basic electronics.

Soft Computing and Signal Processing

Soft Computing and Signal Processing PDF Author: V. Sivakumar Reddy
Publisher: Springer Nature
ISBN: 981198669X
Category : Technology & Engineering
Languages : en
Pages : 669

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Book Description
This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Fifth International Conference on Soft Computing and Signal Processing (ICSCSP 2022). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.

Wireless Sensor Networks

Wireless Sensor Networks PDF Author: Hossam Mahmoud Ahmad Fahmy
Publisher: Springer Nature
ISBN: 3030297004
Category : Technology & Engineering
Languages : en
Pages : 682

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Book Description
This second book by the author on WSNs focuses on the concepts of energy, and energy harvesting and management techniques. Definitions and terminologies are made clear without leaning on the relaxing assumption that they are already known or easily reachable, the reader is not to be diverted from the main course. Neatly drawn figures assist in viewing and imagining the offered topics. To make energy related topics felt and seen, the adopted technologies as well as their manufacturers are presented in details. With such a depth, this book is intended for a wide audience, it is meant to be helper and motivator, for the senior undergraduates, postgraduates, researchers, and practitioners; concepts and energy related applications are laid out, research and practical issues are backed by appropriate literature, and new trends are put under focus. For senior undergraduate students, it familiarizes with conceptual foundations and practical projects implementations. Also, it is intended for graduate students working on their thesis and in need of specific knowledge on WSNs and the related energy harvesting and management techniques. Moreover, it is targeting researchers and practitioners interested in features and applications of WSNs, and on the available energy harvesting and management projects and testbeds. Exercises at the end of each chapter are not just questions and answers; they are not limited to recapitulate ideas. Their design objective is not bound to be a methodical review of the provided concepts, but rather as a motivator for lot more of searching, finding, and comparing beyond what has been presented in the book.

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems PDF Author: K. Suganthi
Publisher: CRC Press
ISBN: 1000441814
Category : Technology & Engineering
Languages : en
Pages : 296

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Book Description
This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.