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Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces…

社会与信息网络 · 计算机科学 2016-11-15 Pin-Yu Chen , Shin-Ming Cheng , Pai-Shun Ting , Chia-Wei Lien , Fu-Jen Chu

Mobile Crowdsensing has shown a great potential to address large-scale problems by allocating sensing tasks to pervasive Mobile Users (MUs). The MUs will participate in a Crowdsensing platform if they can receive satisfactory reward. In…

计算机科学与博弈论 · 计算机科学 2018-08-14 Jiangtian Nie , Zehui Xiong , Dusit Niyato , Ping Wang , Jun Luo

Mobile Crowd-Sensing (MCS) has appeared as a prospective solution for large-scale data collection, leveraging built-in sensors and social applications in mobile devices that enables a variety of Internet of Things (IoT) services. However,…

网络与互联网体系结构 · 计算机科学 2019-04-05 Nguyen Binh Truong , Gyu Myoung Lee , Tai-Won Um , Michael Mackay

Mobile Crowdsensing is a promising paradigm for ubiquitous sensing, which explores the tremendous data collected by mobile smart devices with prominent spatial-temporal coverage. As a fundamental property of Mobile Crowdsensing Systems,…

网络与互联网体系结构 · 计算机科学 2017-01-10 Cong Zhao , Xinyu Yang , Wei Yu , Xianghua Yao , Jie Lin , Xin Li

Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect and upload sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive…

网络与互联网体系结构 · 计算机科学 2014-12-25 Jiajun Sun

The prosperity of smart mobile devices has made mobile crowdsensing (MCS) a promising paradigm for completing complex sensing and computation tasks. In the past, great efforts have been made on the design of incentive mechanisms and task…

多智能体系统 · 计算机科学 2020-11-26 Yize Chen , Hao Wang

Crowd sensing is a new paradigm that leverages pervasive sensor-equipped mobile devices to provide sensing services like forensic analysis, documenting public spaces, and collaboratively constructing statistical models. Extensive user…

社会与信息网络 · 计算机科学 2015-05-26 Jiajun Sun

Worker selection is a significant and challenging issue in crowdsourcing systems. Such selection is usually based on an assessment of the reputation of the individual workers participating in such systems. However, assessing the credibility…

Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond the scale of what was previously possible. In a mobile crowdsensing system, it is paramount to incentivize smartphone users to provide…

网络与互联网体系结构 · 计算机科学 2018-05-01 Francesco Restuccia , Pierluca Ferraro , Simone Silvestri , Sajal K. Das , Giuseppe Lo Re

Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive mechanisms are…

计算机科学与博弈论 · 计算机科学 2014-03-24 Jiajun Sun

Mobile Crowd Sensing (MCS) is the special case of crowdsourcing, which leverages the smartphones with various embedded sensors and user's mobility to sense diverse phenomenon in a city. Task allocation is a fundamental research issue in…

人机交互 · 计算机科学 2018-08-07 Jiangtao Wang , Leye Wang , Yasha Wang , Daqing Zhang , Linghe Kong

Mobile crowdsensing leverages mobile devices (e.g., smart phones) and human mobility for pervasive information exploration and collection; it has been deemed as a promising paradigm that will revolutionize various research and application…

网络与互联网体系结构 · 计算机科学 2013-08-22 Kai Han , Chi Zhang , Jun Luo

Crowdsourcing models applied to work on mobile devices continuously reach new ways of solving sophisticated problems, now with a use of portable advanced devices, where users are not limited to a stationary use. There exists an open problem…

社会与信息网络 · 计算机科学 2015-05-29 Oskar Jarczyk

We propose a mobile crowdsourced sensors selection approach to improve the journey planning service especially in areas where no wireless or vehicular sensors are available. We develop a location estimation model of journey services based…

计算机与社会 · 计算机科学 2018-12-24 Ahmed Ben Said , Abdelkarim Erradi , Azadeh Ghari Neiat , Athman Bouguettaya

Crowdsourcing refers to the arrangement in which contributions are solicited from a large group of unrelated people. Due to this nature, crowdsourcers (or task requesters) often face uncertainty about the workers' capabilities which, in…

多智能体系统 · 计算机科学 2016-01-25 Han Yu

Crowd sensing is a new paradigm which leverages the ubiquity of sensor-equipped mobile devices to collect data. To achieve good quality for crowd sensing, incentive mechanisms are indispensable to attract more participants. Most of existing…

计算机科学与博弈论 · 计算机科学 2014-05-01 Jiajun Sun

Mobile crowdsourced sensing (MCS) is a new paradigm which takes advantage of the pervasive smartphones to efficiently collect data, enabling numerous novel applications. To achieve good service quality for a MCS application, incentive…

计算机科学与博弈论 · 计算机科学 2013-06-25 Dong Zhao , Xiang-Yang Li , Huadong Ma

Mobile crowdsensing engages a crowd of individuals to use their mobile devices to cooperatively collect data about social events and phenomena for special interest customers. It can reduce the cost on sensor deployment and improve data…

密码学与安全 · 计算机科学 2018-06-12 Jianbing Ni , Kuan Zhang , Qi Xia , Xiaodong Lin , Xuemin Shen

Mobile crowdsensing (MCS) is a promising sensing paradigm that leverages the diverse embedded sensors in massive mobile devices. A key objective in MCS is to efficiently schedule mobile users to perform multiple sensing tasks. Prior work…

计算机科学与博弈论 · 计算机科学 2017-05-18 Changkun Jiang , Lin Gao , Lingjie Duan , Jianwei Huang

Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who…

人工智能 · 计算机科学 2024-01-24 Ralf Bruns , Jeremias Dötterl , Jürgen Dunkel , Sascha Ossowski
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