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Participant selection in CrowdSensing environments

机译:人群感应环境中的参与者选择

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CrowdSensing is rooted in Participatory Sensing and crowdsourcing and is defined as a paradigm that harnesses the power of the masses and embedded sensors in smart mobile devices to collect data to be used around a specific target [1]. CrowdSensing has been researched and developed by various authors in different contexts, demonstrating its usefulness to support various processes by offering the ability to generate and maximize the usefulness of the information adding contextual information. This paper presents in an integrated manner the concepts around CrowdSensing and identifies the selection of participants as the main challenge of this paradigm. Finally, a strategy is proposed to address this challenge and how was applied to two case studies.
机译:CrowdSensing植根于参与式感知和众包,被定义为一种范例,它利用大众和智能移动设备中的嵌入式传感器的力量来收集要用于特定目标的数据[1]。 CrowdSensing已经由不同的作者在不同的上下文中进行了研究和开发,通过提供生成和最大化添加上下文信息的信息的功能,证明了CrowdSensing在支持各种过程中的有用性。本文以综合的方式介绍了有关CrowdSensing的概念,并确定了参与者的选择是该范式的主要挑战。最后,提出了应对这一挑战的策略以及如何将其应用于两个案例研究。

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