Vehicle classification in distributed sensor networks
نویسندگان
چکیده
The task of classifying the types of moving vehicles in a distributed, wireless sensor network is investigated. Specifically, based on an extensive real world experiment, we have compiled a dataset that consists of 820 MByte raw time series data, 70 MByte of pre-processed, extracted spectral feature vectors, and baseline classification results using the maximum likelihood classifier. The purpose of this paper is to detail the data collection procedure, the feature extraction and pre-processing steps, and baseline classifier development. The database is available for download at http://www.ece.wisc.edu/∼sensit starting on July 2003.
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عنوان ژورنال:
- J. Parallel Distrib. Comput.
دوره 64 شماره
صفحات -
تاریخ انتشار 2004