A Distributed Intelligent Sensing Approach For Environmental Monitoring Applications

Mots-clés de l'auteur: environmental monitoring ; sensor networks ; mobile sensing.

Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include: Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol.

This book covers two most important applications of smart sensors, namely bio-health sensing and environmental monitoring. The approach taken is holistic and covers the complete scope of the subject matter from the principles of the sensing mechanism, through device physics, circuit and system implementation techniques, and energy issues to wireless connectivity solutions. It is written at a level suitable mainly for post-graduate level researchers interested in practical applications. The chapters are independent but complementary to each other, and the book works within the wider perspective of essential smart sensors for the Internet of Things (IoT). This is the second of three books based on the Integrated Smart Sensors research project, which describe the development of innovative devices, circuits, and system-level enabling technologies. The aim of the project was to develop common platforms on which various devices and sensors can be loaded, and to create systems offering significant improvements in information processing speed, energy usage, and size. This book contains substantial reference lists and over 150 figures, introducing the reader to the subject in a tutorial style whilst also addressing state-of-the-art research results, allowing it to be used as a guide for starting researchers.

The book focuses on the different aspects of sensing technology, i.e. high reliability, adaptability, recalibration, information processing, data fusion, validation and integration of novel and high performance sensors specifically aims to monitor agricultural and environmental parameters. This book is dedicated to Sensing systems for Agricultural and Environmental Monitoring offers to variety of users, namely, Master and PhD degree students, researchers, practitioners, especially Agriculture and Environmental engineers. The book will provide an opportunity of a dedicated and a deep approach in order to improve their knowledge in this specific field.

The rapid development of advanced, arguably, intelligent sensors and their massive deployment provide a foundation for new paradigms to combat the challenges that arise in significant tasks such as positioning, tracking, navigation, and smart sensing in various environments. Relevant advances in artificial intelligence (AI) and machine learning (ML) are also finding rapid adoption by industry and fan the fire. Consequently, research on intelligent sensing systems and technologies has attracted considerable attention during the past decade, leading to a variety of effective applications related to intelligent transportation, autonomous vehicles, wearable computing, wireless sensor networks (WSN), and the internet of things (IoT). In particular, the sensors community has a great interest in novel, intelligent information fusion, and data mining methods coupling AI and ML for substantial performance enhancement, especially for the challenging scenarios that make traditional approaches inappropriate. This reprint book has collected 14 excellent papers that represent state-of-the-art achievements in the relevant topics and provides cutting-edge coverage of recent advances in sensor signal and data mining techniques, algorithms, and approaches, particularly applied for positioning, tracking, navigation, and smart sensing.

This book focuses on the distinct but tightly inter-related areas of development for distributed sensing systems In this book, the authors discuss the technological developments lead by sensor technology, addressing viable new applications to inspire a technological evolution. Under the advanced and visionary approach of distributed intelligence, the authors focus on three distinct but tightly inter-related areas of developments for distributed sensing systems (DSS): firstly, the sensor technology embracing the conversion of the phenomena of interest into desirable form of signal such as electric, secondly, the interaction process between sensing points which requires immense intelligence loosely called networking, and finally, the adoption of useful maturing systems through potential applications for right impacts for a better life and a brighter economy. Furthermore, the book contains a number of case studies and typical applications illustrating the technical details, features and functions of the systems, as well as demonstrating their benefits and limitations. Key Features: Discusses the technological developments lead by sensor technology Addresses viable new applications Contains a number of case studies and typical applications illustrating the technical details, features and functions of the systems Demonstrates the benefits and limitations of distributed sensing Written by experts with vast experience in the field (both in academia and industry) This book will be an invaluable reference for postgraduates studying related courses (communication engineering, engineering management, computer systems, industrial process, automation, design, environmental, urban, surveillance), R&D engineers, system and application designers, researchers, industrial project managers and engineers, and technical and strategic managers planning new products.

Provides an introduction to the topic of smart chemical sensors, along with an overview of the state of the art based on potential applications This book presents a comprehensive overview of chemical sensors, ranging from the choice of material to sensor validation, modeling, simulation, and manufacturing. It discusses the process of data collection by intelligent techniques such as deep learning, multivariate analysis, and others. It also incorporates different types of smart chemical sensors and discusses each under a common set of sub-sections so that readers can fully understand the advantages and disadvantages of the relevant transducers—depending on the design, transduction mode, and final applications. Smart Sensors for Environmental and Medical Applications covers all major aspects of the field of smart chemical sensors, including working principle and related theory, sensor materials, classification of respective transducer type, relevant fabrication processes, methods for data analysis, and suitable applications. Chapters address field effect transistors technologies for biological and chemical sensors, mammalian cell–based electrochemical sensors for label-free monitoring of analytes, electronic tongues, chemical sensors based on metal oxides, metal oxide (MOX) gas sensor electronic interfaces, and more. Addressing the limitations and challenges in obtaining state-of-the-art smart biochemical sensors, this book: Balances the fundamentals of sensor design, fabrication, characterization, and analysis with advanced methods Categorizes sensors into sub-types and describes their working, focusing on prominent applications Describes instrumentation and IoT networking methods of chemical transducers that can be used for inexpensive, accurate detection in commercialized smart chemical sensors Covers monitoring of food spoilage using polydiacetylene- and liposome-based sensors; smart and intelligent E-nose for sensitive and selective chemical sensing applications; odor sensing system; and microwave chemical sensors Smart Sensors for Environmental and Medical Applications is an important book for senior-level undergraduate and graduate students learning about this high-performance technology and its many applications. It will also inform practitioners and researchers involved in the creation and use of smart sensors.

This book is the proceeding of the 1st International Conference on Distributed Sensing and Intelligent Systems (ICDSIS2020) which will be held in The National School of Applied Sciences of Agadir, Ibn Zohr University, Agadir, Morocco on February 01-03, 2020. ICDSIS2020 is co-organized by Computer Vision and Intelligent Systems Lab, University of North Texas, USA as a scientific collaboration event with The National School of Applied Sciences of Agadir, Ibn Zohr University. ICDSIS2020 aims to foster students, researchers, academicians and industry persons in the field of Computer and Information Science, Intelligent Systems, and Electronics and Communication Engineering in general. The volume collects contributions from leading experts around the globe with the latest insights on emerging topics, and includes reviews, surveys, and research chapters covering all aspects of distributed sensing and intelligent systems. The volume is divided into 5 key sections: Distributed Sensing Applications; Intelligent Systems; Advanced theories and algorithms in machine learning and data mining; Artificial intelligence and optimization, and application to Internet of Things (IoT); and Cybersecurity and Secure Distributed Systems. This conference proceeding is an academic book which can be read by students, analysts, policymakers, and regulators interested in Distributed Sensing, Smart Network approaches, Smart Cities, IoT Applications, and Intelligent Applications. It is written in plain and easy language, and describes new concepts when they appear first so that a reader without prior background of the field finds it readable. The book is primarily intended for research students in sensor networks and IoT applications (including intelligent information systems, and smart sensors applications), academics in higher education institutions including universities and vocational colleges, policy makers and legislators.

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications—including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.

This book constitutes the refereed proceedings of the Second International Workshop on Information Processing in Sensor Networks, IPSN 2003, held in Palo Alto, CA, USA, in April 2003. The 23 revised full papers and 21 revised poster papers presented were carefully reviewed and selected from 73 submissions. Among the topics addressed are wireless sensor networks, query processing, decentralized sensor platforms, distributed databases, distributed group management, sensor network design, collaborative signal processing, adhoc sensor networks, distributed algorithms, distributed sensor network control, sensor network resource management, data service middleware, random sensor networks, mobile agents, target tracking, sensor network protocols, large scale sensor networks, and multicast.