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

计算机科学与博弈论 · 计算机科学 2014-04-10 Dong Zhao , Huadong Ma , Liang Liu

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

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 crowd sensing (MCS) is a new paradigm which leverages the ubiquity of sensor-equipped mobile devices such as smartphones, music players, and in-vehicle sensors at the edge of the Internet, to collect data. The new paradigm will fuel…

网络与互联网体系结构 · 计算机科学 2014-10-01 Jiajun Sun

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

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

The recent proliferation of increasingly capable mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to a crowd of participating workers that carry various mobile devices. Aware…

计算机科学与博弈论 · 计算机科学 2017-01-09 Haiming Jin , Lu Su , Klara Nahrstedt

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

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users'…

计算机科学与博弈论 · 计算机科学 2015-04-28 Francesco Restuccia , Sajal K. Das , Jamie Payton

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 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

Crowdsensing, also known as participatory sensing, is a method of data collection that involves gathering information from a large number of common people (or individuals), often using mobile devices or other personal technologies. This…

计算机科学与博弈论 · 计算机科学 2024-05-17 Chattu Bhargavi , Vikash Kumar Singh

Providing an adequate long-term participation incentive is important for a participatory sensing system to maintain enough number of active users (sensors), so as to collect a sufficient number of data samples and support a desired level of…

计算机科学与博弈论 · 计算机科学 2016-11-17 Lin Gao , Fen Hou , Jianwei Huang

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

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 crowdsensing has shown a great potential to address large-scale data sensing problems by allocating sensing tasks to pervasive mobile users. The mobile users will participate in a crowdsensing platform if they can receive…

计算机科学与博弈论 · 计算机科学 2018-11-01 Jiangtian Nie , Jun Luo , Zehui Xiong , Dusit Niyato , Ping Wang

The research on the efforts of combining human and machine intelligence has a long history. With the development of mobile sensing and mobile Internet techniques, a new sensing paradigm called Mobile Crowd Sensing (MCS), which leverages the…

人机交互 · 计算机科学 2014-01-15 Bin Guo , Zhiwen Yu , Daqing Zhang , Xingshe Zhou

Vehicular mobile crowd sensing is a fast-emerging paradigm to collect data about the environment by mounting sensors on vehicles such as taxis. An important problem in vehicular crowd sensing is to design payment mechanisms to incentivize…

计算机科学与博弈论 · 计算机科学 2018-09-17 Susu Xu , Weiguang Mao , Yue Cao , Hae Young Noh , Nihar B. Shah

Mobile crowdsensing (MCS) is a distributed sensing architecture that utilizes existing sensors on mobile units (MUs) to perform sensing tasks. A mobile crowdsensing platform (MCSP) publishes the sensing tasks and the MUs decide whether to…

机器学习 · 计算机科学 2026-05-05 Sumedh J. Dongare , Patrick Weber , Andrea Ortiz , Walid Saad , Oliver Hinz , Anja Klein
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