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Completeness Issues in Mobile Crowd-sensing Environments
Proceedings of the 16th International Conference on Web Information Systems and Technologies, 2020Mobile sensors are being widely used to monitor air quality to quantify human exposure to air pollution. These sensors are prone to malfunctions, resulting in many data quality issues, which in turn impacts the reliability of analytical studies. In this work, we address the problem of data quality evaluation in mobile crowd-sensing environments, and we
Mehanna, Souheir +2 more
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Adaptive and Blind Regression for Mobile Crowd Sensing
IEEE Transactions on Mobile Computing, 2020In mobile crowd sensing (MCS) applications, a public model of a system is expected to be derived from observations collected by mobile device users, through regression modeling. For example, a model describing the relationship between running speed, heart rate, height, and weight of runner can be constructed using MCS data collected from wristbands ...
Shan Chang +3 more
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A Mobility Model for Crowd Sensing Simulation
International Journal of Interdisciplinary Telecommunications and Networking, 2017Mobile Crowd Sensing (MCS) is a class of sensor networks that uses mobile devices for large scale sensing. These networks have some very specific characteristics because of human (smartphone owners) involvement in its operations. Hence, it is important to have a model that takes into account the unique characteristics and opportunities of human ...
Jose Mauricio Nava Auza +1 more
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Mobile crowd sensing based on CICN
2017 International Conference on Information and Communication Technology Convergence (ICTC), 2017In this paper, we propose a Mobile Crowd Sensing application based on Community Information-Centric Networking to collect opportunistic sensing data in limited area where it restricts radius of Bluetooth Low Energy beacon. The application has more valuable features by comparing with common Mobile Crowd Sensing one.
Taewan You +2 more
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Truthful mobile crowd sensing with interdependent valuations
Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, 2020Mobile crowd sensing (MCS) has been used to enable a wide range of resource-discovery applications by exploiting the "wisdom" of many mobile users. However, in many applications, a user's valuation depends on other users' sensory data, which introduces the problem of interdependent valuations.
Meng Zhang 0013 +3 more
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Mobile Crowd Sensing for Solidarity Campaigns
2015We present an ongoing project (This work is partially supported by the InfoCrowds project-PTDC/ECM-TRA/1898/2012 This work is supported by CISUC, via national funding by the FCT - Fundacao para a Ciencia e Tecnologia.) which has two separate strands, one refers to the technological study about the applicability of high performance and high availability
Ana Alves 0001, David Silva
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Staged Incentive Mechanism for Mobile Crowd Sensing
2018 IEEE International Conference on Communications (ICC), 2018In the context of mobile crowd sensing, incentive mechanism is crucial to recruit mobile users to participate in the sensing task and ensure participants to provide high-quality sensing data. In this paper, we investigate a staged incentive mechanism for mobile crowd sensing. We firstly divide the incentive process into two stages: recruiting stage and
Shan Zhong +4 more
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Introduction to Mobile Crowd Sensing
2018In recent years, we have been witnessing the explosive growth of mobile users with sensor-embedded smartphones. Firstly, with the development of wireless communication technology and the increase in personal income, mobile devices (e.g., smartphone, ipad, PDA, etc.) have been becoming more and more popular.
Fen Hou, Yingying Pei, Jingyi Sun
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A Survey of Incentive Techniques for Mobile Crowd Sensing
IEEE Internet of Things Journal, 2015Crowd sensing (CS) is an approach to collecting many samples of a phenomena of interest by distributing the sampling across a large number of individuals. While any one individual may not provide sufficient samples, aggregating samples across many individuals provides high-quality, high-coverage measurements of the phenomena.
Luis Gabriel Jaimes +2 more
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Mobile Crowd Sensing as an Enabler for People as a Service Mobile Computing
2017Mobile Crowd Sensing (MCS) is a new sensing paradigm exploiting the capabilities of smart devices (smartphones, wearables, etc.) to gather large volume of data. Gathering contextual information is a very expensive activity in terms of mobile device resource consumption, so limiting this consumption is essential for user satisfaction.
Paolo Bellavista +3 more
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