CrowdFound

Harburg, Emily; Kim, Yongsung; Gerber, Elizabeth M.; Zhang, Haoqi

doi:10.1145/2702613.2732757

Cited by 6 publications

(7 citation statements)

References 11 publications

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“…In [13] authors security and privacy aspects of mobile crowdsourcing systems [22]. Findings support that potential threats are related to geolocation and biometric information, financial and medical records, as well as submitting personal data for a task completion.…”

Section: ) Other Aspects Of Crowdsourced Systemsmentioning

confidence: 84%

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Circularity Principles in Crowdsourced Systems

Voulgaridis

Angelopoulos

2020

2020 Global Information Infrastructure and Networking Symposium (GIIS)

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High adoption rates of handheld smart devices, such as smartphones, have motivated the rise of crowdsensing methodologies. The corresponding crowdsourced systemssystems whose constituent infrastructure is provided or augmented by the end-users -have been proven very efficient and scalable systems for collecting data from the crowd. However, successfully and sustainably engaging the crowd introduces costs in the form of incentives. Also, the fragmented landscape of crowdsensing applications aggravates the problem of dark data. In this work we address this problem with the introduction of a reference framework for crowdsourced systems that entails circularity principles. Derived from recent developments in Circular Economy, the circularity principles enable the development of crowdsourced systems that are circular by design, by sharing and re-using already existing resources and data. We exemplify the use of the framework via an example use case.

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Section: ) Other Aspects Of Crowdsourced Systemsmentioning

confidence: 84%

“…The goal is for the application to assist and facilitate social interactions. Examples of such applications are [12] and [13].…”

Section: A Applications Of Crowdsourced Systemsmentioning

confidence: 99%

Circularity Principles in Crowdsourced Systems

Voulgaridis

Angelopoulos

2020

2020 Global Information Infrastructure and Networking Symposium (GIIS)

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“…We also review the proposal of locating lost items in some scenarios other than huge crowd gatherings. In [2], authors present CrowdFound, a mobile crowdsourcing system to find lost items. CrowdFound allows users to input lost item descriptions on a map and then sends notifications to users passing near tagged areas [2].…”

Section: Related Workmentioning

confidence: 99%

“…In [2], authors present CrowdFound, a mobile crowdsourcing system to find lost items. CrowdFound allows users to input lost item descriptions on a map and then sends notifications to users passing near tagged areas [2]. A website captioned 'expatriates' [3] allows to advertise and search for advertises posted related to lost and found in Saudi Arabia including Makkah and Madinah but specifically for huge crowd gathering in Hajj.…”

Section: Related Workmentioning

confidence: 99%

“…For example, authors in [11] propose a hybrid Key Item Locating Method to Assist Elderly Daily Life Using the Internet of Things. As the nearest system has been proposed in [4] and [2]. There is a need for using spatial and temporal cues to be integrated with such applications to be able to accurately match missing persons or items as discussed in [6].…”

Section: Related Workmentioning

confidence: 99%

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Spatio-Temporal Modeling and Application for Efficient Online Reporting and Tracking of Lost Items During Huge Crowd Gatherings

Nadeem¹,

Rizwan²,

Syed³

et al. 2020

IJCDS

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Mobile crowdsourcing: framework, challenges, and solutions

Wang

Jia

Jin

et al. 2016

Concurrency and Computation

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Summary Crowdsourcing is the generalized act of outsourcing tasks, traditionally performed by an employee or contractor, to a large group of Internet population through an open call. With the great development of smartphones with rich built‐in sensors and multiple ratio interfaces, mixing smartphone‐based mobile technologies and crowdsourcing offers significant flexibilities and leads to a new paradigm called mobile crowdsourcing (MCS), which can be fully explored for real‐time and location‐sensitive crowdsourced tasks. In this paper, we present a taxonomy for the MCS applications, which are explicitly divided as using human as sensors, and exploiting the wisdom of crowd (i.e., human intelligence). Moreover, two paradigms for mobilizing users in MCS are outlined: direct mode and word of mouth mode. A comprehensive MCS framework and typical workflow of MCS applications are proposed, which consist of nine functional modules, pertaining to three stakeholders in MCS: crowdsourcer, crowdworkers, and crowdsourcing platform. Then, we elaborate the MCS challenges including task management, incentives, security and privacy, and quality control, and summarize the corresponding solutions. Especially, from the viewpoints of various stakeholders, we propose the desired properties that an ideal MCS system should satisfy. The primary goal of this paper is to comprehensively classify and provide a summary on MCS framework, challenges, and possible solutions to highlight the MCS related research topics and facilitate to develop and deploy interesting MCS applications. Copyright © 2016 John Wiley & Sons, Ltd.

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CrowdFound

Cited by 6 publications

References 11 publications

Circularity Principles in Crowdsourced Systems

Circularity Principles in Crowdsourced Systems

Spatio-Temporal Modeling and Application for Efficient Online Reporting and Tracking of Lost Items During Huge Crowd Gatherings

Mobile crowdsourcing: framework, challenges, and solutions

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