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Guest editorial: special issue on mobile crowdsourcing

Bin Guo, Xing Xie, Raghu K. Ganti, Daqing Zhang, Zhu Wang
2018 World wide web (Bussum)  
Crowdsourcing is evolving into a new paradigm, i.e., Mobile Crowdsourcing (MCS), which facilitates the increasing number of mobile device users to participate crowdsourcing tasks.  ...  As a result, quite a number of crowdsourcing tasks that are difficult to complete based on Internet crowdsourcing has now become feasible, e.g., monitoring pollution level or noise level at the city-scale  ...  In "GP-selector: a generic participant selection framework for mobile crowdsourcing systems", the authors develop a generic framework to handle participant selection from the perspective of both task creators  ... 
doi:10.1007/s11280-017-0512-7 fatcat:v6caim3ngvcajmm4k7rn6yvxba

Crowdsourcing with Smartphones

Georgios Chatzimilioudis, Andreas Konstantinidis, Christos Laoudias, Demetrios Zeinalipour-Yazti
2012 IEEE Internet Computing  
for objects generated by a crowd.  ...  We present the intrinsic characteristics of smartphones, a taxonomy that classi es the emerging eld of mobile crowdsourcing and three in-house applications that optimize location-based search and similarity  ...  SmartP2P can be used as a recommender system where the mobile social crowd generates instant information for certain places.  ... 
doi:10.1109/mic.2012.70 fatcat:glqmkflnhvhibgyh6sbvqbsraq

A Feasibility Study on Crowdsourcing to Monitor Municipal Resources in Smart Cities

Thivya Kandappu, Archan Misra, Desmond Koh, Randy Daratan Tandriansyah, Nikita Jaiman
2018 Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18  
In spite of the promise, we believe that the success of such large-scale nation-wide crowdsourcing deployments depend on the real-word user preferences and behavioral characteristics of citizens.  ...  We advocate the importance of matching user mobility patterns against task locations to make the platform more efficient (i.e., higher task completion rate and lower detour overhead).  ...  ACKNOWLEDGEMENT This research is supported by the National Research Foundation, Prime Minister's Office, Singapore under its International Research Centres in Singapore Funding Initiative.  ... 
doi:10.1145/3184558.3191519 dblp:conf/www/KandappuMKTJ18 fatcat:4zylegpgljgtbfrjqpgvrmfqqy

Mobile Crowd Sensing and Computing

Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Y. Yen, Runhe Huang, Xingshe Zhou
2015 ACM Computing Surveys  
This article characterizes the unique features and novel application areas of MCSC and proposes a reference framework for building human-in-the-loop MCSC systems.  ...  We further clarify the complementary nature of human and machine intelligence and envision the potential of deep-fused human-machine systems.  ...  ACKNOWLEDGMENTS The authors would like to thank all the colleagues for their discussion and suggestions.  ... 
doi:10.1145/2794400 fatcat:lol35ouj75eplapvdod5kyy2me

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

Jurairat Phuttharak, Seng W. Loke
2019 IEEE Access  
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  ...  , architectures, and key considerations for their development.  ...  In the task assignment component, the crowdsourcing system should be concerned with assigning the right task to the right workers. For instant, Peng et al.  ... 
doi:10.1109/access.2018.2885353 fatcat:vtfbb7ydjre2rfkulrjm6ypyma

Scalable Urban Mobile Crowdsourcing

Shih-Fen Cheng, Cen Chen, Thivya Kandappu, Hoong Chuin Lau, Archan Misra, Nikita Jaiman, Randy Tandriansyah, Desmond Koh
2017 ACM Transactions on Intelligent Systems and Technology  
The task recommendation platform that we design can match tasks to crowdworkers based on workers' historical trajectories and time budget limits, thus making recommendations personal and efficient.  ...  complete more tasks, and are more efficient against workers relying on their own planning (25% more for top workers who receive recommendations).  ...  ACKNOWLEDGMENTS This research is supported by the National Research Foundation, Prime Minister's Office, Singapore under its International Research Centres in Singapore Funding Initiative, and partially  ... 
doi:10.1145/3078842 fatcat:uwwqtgybcfamxbmwbn5adlgt2m

A Semiopportunistic Task Allocation Framework for Mobile Crowdsensing with Deep Learning

Zhenzhen Xie, Liang Hu, Yan Huang, Junjie Pang, Xiao Zhang
2021 Wireless Communications and Mobile Computing  
The incentive mechanism is for resolving the participant shortage problem, and task assignment methods are studied to find the best match of participants and system utility goal of MCS.  ...  The IoT era observes the increasing demand for data to support various applications and services. The Mobile Crowdsensing (MCS) system then emerged.  ...  In this system, each participant could be a potential worker to accomplish the sensing tasks.  ... 
doi:10.1155/2021/6643229 fatcat:2xi3eavbxrhmjly2k2qer6dvcq

Traffic Regulator Detection and Identification from Crowdsourced Data—A Systematic Literature Review

Stefania Zourlidou, Monika Sester
2019 ISPRS International Journal of Geo-Information  
In the last few years, much research has focused on eliminating such problems by counting on crowdsourced data, such as GPS traces.  ...  these two tasks, (3) to assess the performance of different methods, as well as (4) to identify important aspects of the applicability of these methods.  ...  Good features in general can make a classifier powerful, but certainly bad feature selection can make any classifier incapable of accomplishing even basic recognition tasks.  ... 
doi:10.3390/ijgi8110491 fatcat:dma5dzeww5dpxgfgpq3v2eua7q

HyTasker: Hybrid Task Allocation in Mobile Crowd Sensing [article]

Jiangtao Wang, Feng Wang, Yasha Wang, Leye Wang, Zhaopeng Qiu, Daqing Zhang, Bin Guo, Qin Lv
2018 arXiv   pre-print
In particular, when selecting opportunistic workers in the offline phase of HyTasker, we propose a novel algorithm that simultaneously considers the predicted task assignment for the participatory workers  ...  In the offline phase, a group of workers (called opportunistic workers) are selected, and they complete MCS tasks during their daily routines (i.e., opportunistic mode).  ...  The selected opportunistic workers will collect sensing data for all tasks during their routine trajectories when they connect to the cell towers.  ... 
arXiv:1805.08480v1 fatcat:gc7hkvdbvzbbfdmg6rjcxntam4

Recommandation opportuniste de trajectoires pour l'accomplissement de tâches dans les systèmes crowdsourcing

André Sales Fontenes, Sylvain Bouveret, Jérome Gensel
2016 Document Numérique  
Crowdsourcing market systems (CMS) are platforms that allow one to publish tasks in order to be accomplished by others.  ...  Further, we propose a reference architecture for the deployment of the recommendation of such trajectories in a CMS.  ...  Introduction Au cours des dernières années, de nombreux systèmes de crowdsourcing (CMS, pour Crowdsourcing Market Systems) sont apparus, dans lesquels un groupe d'utilisateurs, appelés exécutants, contribuent  ... 
doi:10.3166/dn.19.1.103-126 fatcat:bgantrf6ijgu3dxwmpbxdt4piq

Co-Tracking: Target Tracking via Collaborative Sensing of Stationary Cameras and Mobile Phones

Zhiyong Yu, Lei Han, Qi An, Huihui Chen, Houchun Yin, Zhiwen Yu
2020 IEEE Access  
Firstly, in order to accurately assign tracking tasks, we propose the Middle Query Location Prediction (MQLP) algorithm for predicting the target's location.  ...  Tracking moving objects in a city, such as suspicious vehicles or persons, is important for public safety management.  ...  Only a few work studies the problem of multi-task allocation. Guo et al. [27] proposed a framework for optimizing the multi-task allocation in a mobile crowdsourcing system. Xiao et al.  ... 
doi:10.1109/access.2020.2979933 fatcat:etruvkmxkzcprkq3kqh7jqqqde

Generalized Lottery Trees: Budget-Consistent Incentive Tree Mechanisms for Crowdsourcing [article]

Dong Zhao, Huadong Ma, Xinna Ji
2018 arXiv   pre-print
Most research assumes that participants are already in the system and aware of the existence of crowdsourcing tasks.  ...  Incentive mechanism design has aroused extensive attention for crowdsourcing applications in recent years.  ...  Most of existing mechanisms assume that participants are already in the system and aware of the existence of crowdsourcing tasks.  ... 
arXiv:1812.09433v1 fatcat:43glbqu3zrfofegc3jyhoicyxm

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions and Opportunities

Andrea Capponi, Claudio Fiandrino, Burak Kantarci, Luca Foschini, Dzmitry Kliazovich, Pascal Bouvry
2019 IEEE Communications Surveys and Tutorials  
For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd.  ...  Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing.  ...  In [169] , the authors propose travel packages exploiting a recommendation system to help users in planning travels by leveraging data collected from crowdsensing.  ... 
doi:10.1109/comst.2019.2914030 fatcat:psvt24nrjbcldpixw6b7stzm3a

Iterative Spatial Crowdsourcing in Peer-to-Peer Opportunistic Networks

Jurairat Phuttharak, Seng W. Loke
2020 Electronics  
This paper proposes and investigates task assignments and recruitment in iterative spatial crowdsourcing processes to find regions of particular interest among a collection of regions.  ...  required) in using such spatial crowdsourcing.  ...  The tasks accomplished by such crowdsourcing may be performed over extended periods of time providing data for analytics, or in an ad-hoc real-time on-demand manner.  ... 
doi:10.3390/electronics9071085 fatcat:7a5zi3mihbcmda34ze4obntx34

Social-Network-Assisted Worker Recruitment in Mobile Crowd Sensing [article]

Jiangtao Wang, Feng Wang, Yasha Wang, Daqing Zhang, Leye Wang, Zhaopeng Qiu
2018 arXiv   pre-print
Worker recruitment is a crucial research problem in Mobile Crowd Sensing (MCS).  ...  We first select a subset of users on the social network as initial seeds and push MCS tasks to them.  ...  INTRODUCTION T HE idea of crowdsourcing rapidly mobilizes large numbers of people to work collectively for accomplishing complicated tasks [1] .  ... 
arXiv:1805.08525v1 fatcat:tfeibluxunajddebq7evd4mfqy
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