When Compressive Sensing Meets Mobile Crowdsensing

When Compressive Sensing Meets Mobile Crowdsensing
Author: Linghe Kong
Publisher: Springer
Total Pages: 127
Release: 2019-06-08
Genre: Computers
ISBN: 9811377766

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.

Mobile Crowdsensing

Mobile Crowdsensing
Author: Cristian Borcea
Publisher: CRC Press
Total Pages: 207
Release: 2016-12-01
Genre: Computers
ISBN: 1315352419

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.

Compressive Sensing for Wireless Networks

Compressive Sensing for Wireless Networks
Author: Zhu Han
Publisher: Cambridge University Press
Total Pages: 308
Release: 2013-06-06
Genre: Computers
ISBN: 1107018838

This comprehensive reference delivers the understanding and skills needed to take advantage of compressive sensing in wireless networks.

Incentive Mechanism for Mobile Crowdsensing

Incentive Mechanism for Mobile Crowdsensing
Author: Youqi Li
Publisher: Springer Nature
Total Pages: 137
Release: 2024-01-03
Genre: Computers
ISBN: 9819969212

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.

Compressive Sensing

Compressive Sensing
Author: Joachim Ender
Publisher: de Gruyter
Total Pages: 365
Release: 2016-05-15
Genre: Mathematics
ISBN: 9783110335316

Compressive Sensing is a new technique in signal processing, enabling imaging systems with limited capabilities in bandwidth or resolution to recover "natural?" signals with high accuracy. This graduate textbook provides detailed background for study and research in compressive sensing, including signal models, measurement schemes, recovery algorithms, highlighting recent theoretical results and showing a broad range of applications.

Mobile Crowd Sensing

Mobile Crowd Sensing
Author: Fen Hou
Publisher:
Total Pages:
Release: 2019
Genre: Intelligent sensors
ISBN: 9783030010256

This SpringerBrief investigates and reviews the development and various applications of mobile crowd sensing (MCS). With the miniaturization of sensors and the popularity of smart mobile devices, MCS becomes a promising solution to efficiently collect different types of information, such as traffic conditions, air quality, temperature and more, which is covered in this brief. The features, novelty, and applications of MCS are elaborated in detail in this brief. In addition, the basic knowledge about auction theory and incentive mechanism design is introduced. Incentive mechanism design plays a key role in the success of MCS. With an efficient incentive mechanism, it is possible to attract enough mobile users to participate in a MCS system, thus enough high quality sensing data can be collected. Two types of incentive mechanisms with different system models are introduced in this brief. One is the reputation-aware incentive mechanism, and another is the social-aware incentive mechanism. This SpringerBrief covers the significance and the impacts of both reputation and social relationship of smartphone users (SUs) in MCS and presents extensive simulation results to demonstrate the good performance of the proposed incentive mechanisms compared with some existing counterparts. The target audience for this SpringerBrief is researchers and engineers in the area of wireless communication and networking, especially those who are interested in the mobile crowd sensing or incentive mechanism design. Meanwhile, it is also intended as a reference guide for advanced level students in the area of wireless communications and computer networks.

Mobile Crowdsourcing

Mobile Crowdsourcing
Author: Jie Wu
Publisher: Springer Nature
Total Pages: 456
Release: 2023-07-16
Genre: Computers
ISBN: 3031323971

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.

Compressive Sensing for Wireless Communication

Compressive Sensing for Wireless Communication
Author: Radha Sankararajan
Publisher: CRC Press
Total Pages: 0
Release: 2022-09-01
Genre: Technology & Engineering
ISBN: 100079122X

Compressed Sensing (CS) is a promising method that recovers the sparse and compressible signals from severely under-sampled measurements. CS can be applied to wireless communication to enhance its capabilities. As this technology is proliferating, it is possible to explore its need and benefits for emerging applicationsCompressive Sensing for Wireless Communication provides:• A clear insight into the basics of compressed sensing• A thorough exploration of applying CS to audio, image and computer vision• Different dimensions of applying CS in Cognitive radio networks• CS in wireless sensor network for spatial compression and projection• Real world problems/projects that can be implemented and tested• Efficient methods to sample and reconstruct the images in resource constrained WMSN environmentThis book provides the details of CS and its associated applications in a thorough manner. It lays a direction for students and new engineers and prepares them for developing new tasks within the field of CS. It is an indispensable companion for practicing engineers who wish to learn about the emerging areas of interest.

Social Sensing

Social Sensing
Author: Dong Wang
Publisher: Morgan Kaufmann
Total Pages: 232
Release: 2015-04-17
Genre: Computers
ISBN: 0128011319

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