Mobile Crowdsensing
Mobile Crowdsensing

Author: Cristian Borcea

Publisher: CRC Press

Published: 2016-12-01

Total Pages: 207

ISBN-13: 1315352419

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Mobile crowdsensing is a technology that allows large scale, cost-effective sensing of the physical world. In mobile crowdsensing, mobile personal devices such as smart phones or smart watches come equipped with a variety of sensors that can be leveraged to collect data related to environment, transportation, healthcare, safety and so on. This book presents the first extensive coverage of mobile crowdsensing, with examples and insights drawn from the authors’ extensive research on this topic as well as from the research and development of a growing community of researchers and practitioners working in this emerging field. Throughout the text, the authors provide the reader with various examples of crowdsensing applications and the building blocks to creating the necessary infrastructure, explore the related concepts of mobile sensing and crowdsourcing, and examine security and privacy issues introduced by mobile crowdsensing platforms. Provides a comprehensive description of mobile crowdsensing, a one-stop shop for all relevant issues pertaining to mobile crowdsensing, including motivation, applications, design and implementation, incentive mechanisms, and reliability and privacy. Describes the design and implementations of mobile crowdsensing platforms of great interest for the readers working in research and industry to quickly implement and test their systems. Identifies potential issues in building such mobile crowdsensing applications to ensure their usability in real life and presents future directions in mobile crowdsensing by emphasizing the open problems that have to be addressed.

When Compressive Sensing Meets Mobile Crowdsensing
When Compressive Sensing Meets Mobile Crowdsensing

Author: Linghe Kong

Publisher: Springer

Published: 2019-06-08

Total Pages: 134

ISBN-13: 9811377766

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This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data. Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don’t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.

Incentive Mechanism for Mobile Crowdsensing
Incentive Mechanism for Mobile Crowdsensing

Author: Youqi Li

Publisher: Springer Nature

Published: 2024-01-03

Total Pages: 137

ISBN-13: 9819969212

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Mobile crowdsensing (MCS) is emerging as a novel sensing paradigm in the Internet of Things (IoTs) due to the proliferation of smart devices (e.g., smartphones, wearable devices) in people’s daily lives. These ubiquitous devices provide an opportunity to harness the wisdom of crowds by recruiting mobile users to collectively perform sensing tasks, which largely collect data about a wide range of human activities and the surrounding environment. However, users suffer from resource consumption such as battery, processing power, and storage, which discourages users’ participation. To ensure the participation rate, it is necessary to employ an incentive mechanism to compensate users’ costs such that users are willing to take part in crowdsensing. This book sheds light on the design of incentive mechanisms for MCS in the context of game theory. Particularly, this book presents several game-theoretic models for MCS in different scenarios. In Chapter 1, the authors present an overview of MCS and state the significance of incentive mechanism for MCS. Then, in Chapter 2, 3, 4, and 5, the authors propose a long-term incentive mechanism, a fair incentive mechanism, a collaborative incentive mechanism, and a coopetition-aware incentive mechanism for MCS, respectively. Finally, Chapter 6 summarizes this book and point out the future directions. This book is of particular interest to the readers and researchers in the field of IoT research, especially in the interdisciplinary field of network economics and IoT.

Social Sensing
Social Sensing

Author: Dong Wang

Publisher: Morgan Kaufmann

Published: 2015-04-17

Total Pages: 232

ISBN-13: 0128011319

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Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book

Privacy-Preserving in Mobile Crowdsensing
Privacy-Preserving in Mobile Crowdsensing

Author: Chuan Zhang

Publisher: Springer Nature

Published: 2023-03-24

Total Pages: 205

ISBN-13: 9811983151

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Mobile crowdsensing is a new sensing paradigm that utilizes the intelligence of a crowd of individuals to collect data for mobile purposes by using their portable devices, such as smartphones and wearable devices. Commonly, individuals are incentivized to collect data to fulfill a crowdsensing task released by a data requester. This “sensing as a service” elaborates our knowledge of the physical world by opening up a new door of data collection and analysis. However, with the expansion of mobile crowdsensing, privacy issues urgently need to be solved. In this book, we discuss the research background and current research process of privacy protection in mobile crowdsensing. In the first chapter, the background, system model, and threat model of mobile crowdsensing are introduced. The second chapter discusses the current techniques to protect user privacy in mobile crowdsensing. Chapter three introduces the privacy-preserving content-based task allocation scheme. Chapter four further introduces the privacy-preserving location-based task scheme. Chapter five presents the scheme of privacy-preserving truth discovery with truth transparency. Chapter six proposes the scheme of privacy-preserving truth discovery with truth hiding. Chapter seven summarizes this monograph and proposes future research directions. In summary, this book introduces the following techniques in mobile crowdsensing: 1) describe a randomizable matrix-based task-matching method to protect task privacy and enable secure content-based task allocation; 2) describe a multi-clouds randomizable matrix-based task-matching method to protect location privacy and enable secure arbitrary range queries; and 3) describe privacy-preserving truth discovery methods to support efficient and secure truth discovery. These techniques are vital to the rapid development of privacy-preserving in mobile crowdsensing.

Mobile Crowdsourcing
Mobile Crowdsourcing

Author: Jie Wu

Publisher: Springer Nature

Published: 2023-07-16

Total Pages: 456

ISBN-13: 3031323971

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This book offers the latest research results in recent development on the principles, techniques and applications in mobile crowdsourcing. It presents state-of-the-art content and provides an in-depth overview of the basic background in this related field. Crowdsourcing involves a large crowd of participants working together to contribute or produce goods and services for the society. The early 21st century applications of crowdsourcing can be called crowdsourcing 1.0, which includes businesses using crowdsourcing to accomplish various tasks, such as the ability to offload peak demand, access cheap labor, generate better results in a timely matter, and reach a wider array of talent outside the organization. Mobile crowdsensing can be described as an extension of crowdsourcing to the mobile network to combine the idea of crowdsourcing with the sensing capacity of mobile devices. As a promising paradigm for completing complex sensing and computation tasks, mobile crowdsensing serves the vital purpose of exploiting the ubiquitous smart devices carried by mobile users to make conscious or unconscious collaboration through mobile networks. Considering that we are in the era of mobile internet, mobile crowdsensing is developing rapidly and has great advantages in deployment and maintenance, sensing range and granularity, reusability, and other aspects. Due to the benefits of using mobile crowdsensing, many emergent applications are now available for individuals, business enterprises, and governments. In addition, many new techniques have been developed and are being adopted. This book will be of value to researchers and students targeting this topic as a reference book. Practitioners, government officials, business organizations and even customers -- working, participating or those interested in fields related to crowdsourcing will also want to purchase this book.

Digital Phenotyping and Mobile Sensing
Digital Phenotyping and Mobile Sensing

Author: Christian Montag

Publisher: Springer Nature

Published: 2022-07-22

Total Pages: 466

ISBN-13: 3030985466

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This book offers a snapshot of cutting-edge applications of digital phenotyping and mobile sensing for studying human behavior and planning innovative e-healthcare interventions. The respective chapters, written by authoritative researchers, cover both theoretical perspectives and good scientific and professional practices related to the use and development of these technologies. They share novel insights into established applications of mobile sensing, such as predicting personality or mental and behavioral health on the basis of smartphone usage patterns, and highlight emerging trends, such as the use of machine learning, big data and deep learning approaches, and the combination of mobile sensing with AI and expert systems. Important issues relating to privacy and ethics are analyzed, together with selected case studies. This thoroughly revised and extended second edition provides researchers and professionals with extensive information on the latest developments in the field of digital phenotyping and mobile sensing. It gives a special emphasis to trends in diagnostics systems and AI applications, suggesting important future directions for research in public health and social sciences.

Mobile Computing, Applications, and Services
Mobile Computing, Applications, and Services

Author: Yuyu Yin

Publisher: Springer Nature

Published: 2019-09-24

Total Pages: 245

ISBN-13: 3030284689

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This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2019, held in Hangzhou, China, in June 2019. The 17 full papers were carefully reviewed and selected from 48 submissions. The papers are organized in topical sections on mobile application with data analysis, mobile application with AI, edge computing, energy optimization and application

Security and Privacy for Next-Generation Wireless Networks
Security and Privacy for Next-Generation Wireless Networks

Author: Sheng Zhong

Publisher: Springer

Published: 2018-11-22

Total Pages: 194

ISBN-13: 303001150X

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This timely book provides broad coverage of security and privacy issues in the macro and micro perspective. In macroperspective, the system and algorithm fundamentals of next-generation wireless networks are discussed. In micro-perspective, this book focuses on the key secure and privacy techniques in different emerging networks from the interconnection view of human and cyber-physical world. This book includes 7 chapters from prominent international researchers working in this subject area. This book serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to wireless security and privacy related issues Recent advances in wireless communication technologies have enabled the large-scale deployment of next-generation wireless networks, and many other wireless applications are emerging. The next generation of mobile networks continues to transform the way people communicate and access information. As a matter of fact, next-generation emerging networks are exploiting their numerous applications in both military and civil fields. For most applications, it is important to guarantee high security of the deployed network in order to defend against attacks from adversaries, as well as the privacy intrusion. The key target in the development of next-generation wireless networks is to promote the integration of the human, cyber, and physical worlds. Previous work in Cyber Physical Systems (CPS) considered the connection between the cyber world and the physical world. In the recent studies, human involvement brings new channels and initiatives in this interconnection. In this integration process, security and privacy are critical issues to many wireless network applications, and it is a paramount concern for the growth of next-generation wireless networks. This is due to the open nature of wireless communication and the involvement of humans. New opportunities for tackling these security and privacy issues in next-generation wireless networks will be achieved by leveraging the properties of interaction among human, computers and things.