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008			230717s2023 sz | o |||| 0|eng d
020			_a9783031323973
024	7		_a10.1007/978-3-031-32397-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5105.5 _b2023 EB
245	0	0	_aMobile Crowdsourcing : _bFrom Theory to Practice _cedited by Jie Wu, En Wang
250			_a1st ed 2023
264		1	_aCham _bSpringer International Publishing _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aWireless Networks _x2366-1445
505	0		_aCrowdsourcing as a Future Collaborative Computing Paradigm -- Urban Mobility-Driven Crowdsensing: Recent Advances in Machine Learning Designs and Ubiquitous Applications -- Unknown User Recruitment in Mobile Crowdsourcing -- Quality-Aware Incentive Mechanism for Mobile Crowdsourcing -- Incentive mechanism design for mobile crowdsourcing without verification -- Stable Worker-Task Assignment in Mobile Crowdsensing Applications -- Spatio temporal Task Allocation in Mobile Crowdsensing -- Joint Data Collection and Truth Inference in Spatial Crowdsourcing -- Cost-quality Aware Compressive Mobile Crowdsensing -- Information Integrity in Participatory Crowd-Sensing via Robust Trust Models -- AI-Driven Attack Modeling and Defence Strategies in Mobile Crowdsensing: A special Case Study on Fake Tasks -- Traceable and Secure Data Sharing in Mobile Crowdsensing -- User Privacy Protection in MCS: Threats, Solutions and Open Issues -- Crowdsourcing Through TinyML as aWay to Engage End-users in IoT Solutions -- Health Crowd Sensing and Computing: From Crowdsourced Digital Health Footprints to Population Health Intelligence -- Crowdsourcing Applications and Techniques in Computer Vision -- Mobile Crowdsourcing Task Offloading on Social Collaboration Networks: An Empirical Study.
520			_aThis 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.
988			_aSpringer_Computer_2023
650		7	_2embne _9141354 _aRedes informáticas
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-32397-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2024 _dz _eb _zSI