Abstract
Real-time and fine-grained rain information is crucial not only for climate research, weather prediction, water resources management, agricultural production, urban planning and natural disasters monitoring, but also for applications in our daily lives. However, because of the lack of rain detection systems and the high variable attribute of rain, both in time and space, the rain detection today is still not precise enough. In such context, we propose and implement Tefnut (Tefnut is the rain deity in Ancient Egyptian religion.), a novel system that exploits opportunistically crowdsourced in-vehicle audio clips from an alternative, nowadays omnipresent source, smartphones, to achieve precise detection of rain leveraging a supervised recognizer constructed from a series of refined features. We conduct extensive experiments, and evaluation results demonstrate that Tefnut can detect the rain with 96.0 % true positive rate, when deciding with a one-second-long in-vehicle audio segment only.
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Notes
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In this paper, the superscript
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or 
on a variable indicates that this variable is calculated in power spectrum, time domain or frequency spectrum respectively.
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or 
on a variable indicates that this variable is calculated in power spectrum, time domain or frequency spectrum respectively.References
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Acknowledgement
This paper was supported by National Natural Science Foundation of China under Grant No. 61572342, 61303206 and 61472384, Natural Science Foundation of Jiangsu Province under Grant No. BK20151240 and BK20140395, China Postdoctoral Science Foundation under Grant No. 2015M580470.
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Guo, H. et al. (2016). Tefnut: An Accurate Smartphone Based Rain Detection System in Vehicles. In: Yang, Q., Yu, W., Challal, Y. (eds) Wireless Algorithms, Systems, and Applications. WASA 2016. Lecture Notes in Computer Science(), vol 9798. Springer, Cham. https://doi.org/10.1007/978-3-319-42836-9_2
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DOI: https://doi.org/10.1007/978-3-319-42836-9_2
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