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Multimedia Sensor Networks

verfasst von: Prof. Huadong Ma, Prof. Liang Liu, Prof. Hong Luo

Verlag: Springer Singapore

Buchreihe : Advances in Computer Science and Technology

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Sensor networks are an essential component of the Internet of Things (IoT), and Multimedia Sensor Networks (MSNs) are the most important emerging area in sensor networks. However, multimedia sensing is characterized by diversified modes, large volumes of data, considerable heterogeneity, and complex computing, as a result of which the theory and methods for traditional sensor networks can’t be applied to MSNs.

Based on the authors’ years of systematic research on related theory and methods, this book provides a comprehensive review of MSNs. The coverage ranges from networked sensing and fusion-based transmission, to route discovery and in-network computing. The book presents the most important scientific discoveries and fundamental theories on MSNs, while also exploring practical approaches and typical applications. Given its scope, it is especially suitable for students, researchers and practitioners interested in understanding scientific problems involved in characterizing multimedia sensing features, revealing the transmission mechanisms of MSNs, and constructing efficient in-network multimedia computing paradigms. In this book, readers will learn essential methods for achieving the optimal deployment of, efficient and reliable transmission, and timely information processing in MSNs.

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Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction to Multimedia Sensor Networks

Abstract

Multimedia Sensor Networks (MSNs), being capable of gathering the visual and acoustic information from the surrounding environment, has opened a new vision to traditional wireless sensor networks by enhancing its existing capability. This chapter introduces the basic concepts of MSNs, and describes the conceptual architecture. The main research topics of MSNs are also discussed as the five aspects: network architecture, deployment and coverage control, fusion transmission of multimedia, in-network information processing, and typical applications and IoT services.

Huadong Ma, Liang Liu, Hong Luo

Chapter 2. Directional Sensing Models and Coverage Control

Abstract

“How well do the sensors observe the physical space?” is a fundamental problem for designing a sensing system. Considering some commonly used sensors (the typical example is camera sensor) with the FoV (field of view) limitation, this chapter defines 2D and 3D directional sensing model, and then design a potential field based method to maximize the coverage by adjusting sensors’ orientations under the random deployment strategy. Furthermore, this chapter presents the concepts of Directional K-Coverage (DKC) and Localization-oriented coverage (L-coverage) for MSNs. They are different from the coverage problem in conventional sensor networks due to combining the directionality of sensing model and the sensing requirements of target recognition/localization. This chapter also discusses the partial coverage by applying the percolation theory to solve the exposure path problem for MSNs.

Huadong Ma, Liang Liu, Hong Luo

Chapter 3. Data Fusion Based Transmission in Multimedia Sensor Networks

Abstract

While in-network data fusion can reduce data redundancy and hence curtail network load, the fusion process itself may introduce significant energy consumption for multimedia sensor networks. How to balance the aggregation cost and transmission cost becomes the main challenge. This chapter presents a routing algorithm, Adaptive Fusion Steiner Tree (AFST), for energy efficient data gathering. The data fusion routing can be modelled as the Steiner tree problem. Inspired by the cellular computing model in the slime mold physarum polycephalum, this chapter develops a optimization algorithm, physarum optimization, with low-complexity and high parallelism to solve the Steiner tree problem. Moreover, this chapter designs a trust based framework for data aggregation by jointly considering data aggregation, information trust and fault tolerance to enhance the correctness and trustworthiness of collected information.

Huadong Ma, Liang Liu, Hong Luo

Chapter 4. In-Network Processing for Multimedia Sensor Networks

Abstract

Transmission and processing of multimedia data are not independent. The in-network processing mode has a major impact on energy aware multimedia processing algorithms and energy efficient transmission in order to maximize network lifetime while meeting application requirements. This chapter presents three collaborative in-network processing schemes for visual information collection, target tracking, and target recognition, respectively. Then, a computing mode, decomposition-fusion (DF), and a cooperative framework are proposed to support that the complex task of MSNs can be efficiently divided into a set of subtasks and the suitable multimedia sensor nodes can be selected to execute the subtasks in the cooperative fashion.

Huadong Ma, Liang Liu, Hong Luo

Chapter 5. Multimedia Sensor Network Supported IoT Service

Abstract

Because of the ability to ubiquitously capture multimedia content from the environment, multimedia sensor networks have great potential for strengthening the traditional wireless sensor networks applications, as well as creating a series of new applications. After introducing three typical service patterns of IoT, information publish service, sensing-controlling service, and IoT search service, this chapter focuses on the IoT search and proposes a progressive search paradigm, which contains three important search strategies: (1) coarse-to-fine search in feature space; (2) near-to-distant search in spatial-temporal space; and (3) low-to-high permission search in the security space. This chapter also proposes a progressive vehicle re-identification framework based on deep neural networks.

Huadong Ma, Liang Liu, Hong Luo

Chapter 6. Prospect of Future Research

Abstract

This chapter concludes the current challenges and research directions of IoT sensing. The main direction is deeply combining with the new-generation AI theories and technologies to improve the intelligence of IoT. This chapter analyzes the three specifical challenges of human-like perception, intelligent networking and transmission, and intelligent services in detail.

Huadong Ma, Liang Liu, Hong Luo

Titel: Multimedia Sensor Networks
verfasst von: Prof. Huadong Ma
Prof. Liang Liu
Prof. Hong Luo
Copyright-Jahr: 2021
Verlag: Springer Singapore
Electronic ISBN: 978-981-16-0107-1
Print ISBN: 978-981-16-0106-4
DOI: https://doi.org/10.1007/978-981-16-0107-1

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