EnUp: Energy-Efficient Data Uploading for Mobile Crowd Sensing Applications. Abstract: Mobile crowd sensing enables large-scale sensing of the physical world at low cost by leveraging the available sensors on the mobile phones.
Mobile crowd sensing enables large-scale sensing of the physical world at low cost by leveraging the available sensors on the mobile phones.
Piggyback CrowdSensing is proposed, a system for collecting mobile sensor data from smartphones that lowers the energy overhead of user participation and ...
We will demonstrate, from both synthetic and real data, that our methods achieve high sensing coverage with low cost using cloaked participant locations. We ...
May 9, 2019 · EnUp: Energy-Efficient Data. Uploading for Mobile Crowd Sensing Applications. International. Workshop on Crowd Intelligence for Smart Cities ...
Dec 1, 2022 · In this paper, we propose several algorithms to choose a minimum number of mobile users(or participants) who met the desired level of coverage.
novel approach to coverage for mobile crowd sensing systems,” in ... Pan, “Enup: Energy-efficient data uploading for mobile crowd sensing applications,” in UIC- ...
Energy-Efficient Distributed Mobile Crowd Sensing: A Deep Learning Approach · An adaptive energy efficient flow coverage scheme for mobile crowd sensing in urban ...
Besides, Wang et al. [54] propose a data uploading framework to minimize the energy consumption and data cost when upload the sensing data. The framework named ...
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In this article, we propose a new crowdsensing paradigm, sparse mobile crowdsensing, which leverages the spatial and temporal correlation among the data sensed ...