JOURNAL ARTICLE

StreamShaper: Coordination algorithms for participatory mobile urban sensing

Abstract

\n In this paper we introduce mechanisms for automated mapping of urban\n areas that provide a virtual sensor abstraction to the applications.\n We envision a participatory system that exploits widely available\n devices as mobile phones to cooperatively read environmental\n conditions as air quality or noise pollution, and map these\n measurements to stationary virtual sensors. We propose spatial and\n temporal coverage metrics for measuring the quality of acquired\n sensor data that reflect the conditions of urban areas and the\n uncontrolled movement of nodes. To achieve quality requirements and\n efficiency in terms of energy consumption, this paper presents two\n algorithms for coordinating sensing. The first is based on a central\n control instance, which assigns sensing tasks to mobile nodes based\n on movement predictions. The second algorithm is based on\n coordination of mobile nodes in an ad-hoc network. By extensive\n simulations, we show that these algorithms achieve a high quality of\n readings, which is about 95% of the maximum possible. Moreover, the\n algorithms achieve a very high energy efficiency allowing for\n drastic savings compared to uncoordinated sensing.\n

Keywords:
Computer science Participatory sensing Energy consumption Wireless sensor network Mobile device Distributed computing Exploit Abstraction Efficient energy use Mobile computing Quality (philosophy) Real-time computing Wireless ad hoc network Noise (video) Computer network Artificial intelligence Wireless Telecommunications Computer security Data science Engineering

Metrics

48
Cited By
18.47
FWCI (Field Weighted Citation Impact)
19
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Mobile Crowdsensing and Crowdsourcing
Physical Sciences →  Computer Science →  Computer Science Applications
Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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