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2014 28th International Conference on Advanced Information Networking and Applications Workshops (WAINA) (2014)
BC, Canada
May 13, 2014 to May 16, 2014
ISBN: 978-1-4799-2652-7
pp: 67-72
ABSTRACT
This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.
INDEX TERMS
Wireless Sensor Network, Machine Learning, Flash Flood Nowcasting
CITATION

G. Furquim et al., "Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting," 2014 28th International Conference on Advanced Information Networking and Applications Workshops (WAINA), BC, Canada, 2014, pp. 67-72.
doi:10.1109/WAINA.2014.21
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