Mobile Crowdsourcing: Architecture, Applications, and Challenges

Wang, Yufeng; Jia, Xueyu; Jin, Qun; Ma, Jun

doi:10.1109/uic-atc-scalcom-cbdcom-iop.2015.206

Cited by 8 publications

(8 citation statements)

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“…Then, the challenges in MCS systems and corresponding solutions are discussed, including task management, incentives, security and privacy, and quality control. Especially, from various viewpoints of stakeholders, this paper comprehensively summarizes the desired properties that MCS systems should satisfy.Note that our previous work preliminarily investigated the MCS architectures, some typical applications, and challenges [5]. This paper significantly extended our previous work in the following aspects: incorporate the two mobilization modes (i.e., direct and WoM) into the proposed MCS framework, investigate the desired properties that a MCS system should satisfy from different stakeholders' viewpoints, and present several typical integrated schemes that simultaneously consider and solve several challenges, and meet multiple properties.The paper is structured as follows.…”

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confidence: 81%

“…Note that our previous work preliminarily investigated the MCS architectures, some typical applications, and challenges [5]. This paper significantly extended our previous work in the following aspects: incorporate the two mobilization modes (i.e., direct and WoM) into the proposed MCS framework, investigate the desired properties that a MCS system should satisfy from different stakeholders' viewpoints, and present several typical integrated schemes that simultaneously consider and solve several challenges, and meet multiple properties.…”

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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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confidence: 81%

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confidence: 81%

Mobile crowdsourcing: framework, challenges, and solutions

Wang

Jia

Jin

et al. 2016

Concurrency and Computation

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“…In this review, we explore mobile crowdsourcing applications with regards to four key aspects. Yufeng et al [25] and Wang et al [26] study on the building blocks of mobile crowdsourcing systems. As they mentioned, the crowdsourcing system needs to address a number of fundamental challenges including quality control, task management, incentives, as well as security and privacy.…”

Section: Key Aspects Of Mobile Crowdsourcing Applicationsmentioning

confidence: 99%

“…However, mobile crowdsourcing systems still face many challenges with regards to security, privacy and trust [23], [38]. The common privacy and security threats include: disclosing user identity, location and activity, combining crowdsourced data with other user data, lack of user privacy awareness, vulnerability of mobile devices, relying on information that may be inaccurate, and retaliation for reporting sensitive information [26], [113], [114].…”

Section: ) Crowd Processing Layermentioning

confidence: 99%

A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-Things

Phuttharak

Loke

2019

IEEE Access

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Crowdsourcing using mobile devices, known as mobile crowdsourcing, is a powerful approach incorporating human wisdom into mobile computations to solve problems while exploiting the advantages of mobility and context-awareness. The problems that can be tackled include the use of geographically distributed tasks, and mobile sensing using the collective wisdom of the crowd. However, the implementation of mobile crowdsourcing applications has been found to be challenging to users due to the nature of dynamic sensing, crowd engagement with data distribution, and a process of data verification. In this paper, we provide an extensive survey of the literature on mobile crowdsourcing research, highlighting the aspects of particular concerns in terms of implementation needs during the development, architectures, and key considerations for their development. We present a taxonomy based on the key issues in mobile crowdsourcing and discuss the different approaches applied to these issues. We also provide a critical analysis of some challenges and suggest directions for future work. In particular, with the future Internet-of-Things in view, we generalize the notion of mobile crowdsourcing to thing crowdsourcing, where crowdsourcing can be issued from smart Internet-connected things that need to harness the human resources to solve problems.

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“…Further, the success of gamification in crowdsourcing systems is undeniable. Crowdsourcing services are excellent for accomplishing activities that are simple for humans but difficult for machines (Wang et al , 2016) and make a large number of stakeholders more accessible (Snijders et al , 2015). Besides, as mentioned before, gamification is to keep users motivated through rewarding the useful participants (Snijders et al , 2015).…”

Section: Introductionmentioning

confidence: 99%

Kiyaslio: a gamified mobile crowdsourcing application for tracking price dispersion in the grocery retail market

Macakoğlu

Çınar

Peker

2022

IJWIS

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Purpose In the recent years, the rapid growth of the grocery retailing industry has created a great heterogeneity in prices across sellers in the market. Online price comparison agents which are key mechanisms to solve this problem by providing prices from different sellers. However, there are many sellers in the grocery industry do not offer online service, and so it is impossible to automatically retrieve price information from such grocery stores. In this manner, crowdsourcing can become an essential source of information by collecting current price data from shoppers. Therefore, this paper aims to propose Kiyaslio, a gamified mobile crowdsourcing application that provides price information of products from different grocery markets. Design/methodology/approach Kiyaslio has been developed through leveraging the power of crowdsourcing technology. Game elements have also been used to increase the willingness of users to contribute on price data entries. The proposed application is implemented using design science methodology, and it has been evaluated through usability testing by two well-known techniques which are the system usability scale and the net promoter score. Findings The results of the usability tests indicate that participants find Kiyaslio as functional, useful and easy to use. These findings prove its applicability and user acceptability. Practical implications The proposed platform supports crowd sourced data collection and could be effectively used as a tool to support shoppers to easily access current market product prices. Originality/value This paper presents a mobile application platform for tracking current prices in the grocery retail market whose strength is based on the crowdsourcing concept and incorporation of game elements.

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Mobile Crowdsourcing: Architecture, Applications, and Challenges

Cited by 8 publications

References 9 publications

Mobile crowdsourcing: framework, challenges, and solutions

Mobile crowdsourcing: framework, challenges, and solutions

A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-Things

Kiyaslio: a gamified mobile crowdsourcing application for tracking price dispersion in the grocery retail market

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