ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Anomaly Detection in Taxi Flow by a Projection Method

Myeong-Hun Jeong, Seung-Bae Jeon, Sangjun Park, and Sanggu Kang

(Received August 25, 2019; Accepted October 16, 2019)

Keywords: trajectory outliers, projection method, trajectory data mining, outlier detection

The prevalence of location-aware devices has increased the analysis of movement data. In this study, we investigated anomaly detection in taxi trajectories. A projection method was used to detect trajectory outliers. This is a robust statistical method and considers two dimensions of data simultaneously—distance and time. The experimental data included taxi movements in Seoul City and New York City. The results were compared with those of an alternative method, the Mahalanobis distance approach. The findings were observed to be similar. The proposed method can be used to improve the services of taxis and buses.

Corresponding author: Sangjun Park




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