期刊名称：Journal of Computing and Information Technology
印刷版ISSN：1330-1136
电子版ISSN：1846-3908
出版年度：2010
卷号：18
期号：4
页码：341-347
DOI：10.2498/cit.1001913
出版社：SRCE - Sveučilišni računski centar
摘要：Extracting useful information from raw sensor data requires specific methods and algorithms. We describe a vertical system integration of a sensor node and a toolkit of machine learning algorithms for predicting the number of persons located in a closed space. The dataset used as input for the learning algorithms is composed of automatically collected sensor data and additional manually introduced data. We analyze the dataset and evaluate the performance of two types ofmachine learning algorithms on this dataset: classification and regression. With our system settings, the experiments show that augmenting sensor data with proper information can improve prediction results and also the classification algorithm performed better.
关键词：sensor node; data mining; machine learning; prediction
