Research Article
Anomalous Taxi Route Detection System Based on Cloud Services
@INPROCEEDINGS{10.1007/978-3-030-48513-9_20, author={Yu Zi and Yun Luo and Zihao Guang and Lianyong Qi and Taoran Wu and Xuyun Zhang}, title={Anomalous Taxi Route Detection System Based on Cloud Services}, proceedings={Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. 9th EAI International Conference, CloudComp 2019, and 4th EAI International Conference, SmartGIFT 2019, Beijing, China, December 4-5, 2019, and December 21-22, 2019}, proceedings_a={CLOUDCOMP}, year={2020}, month={6}, keywords={Anomaly detection Taxi route Cloud service Machine learning}, doi={10.1007/978-3-030-48513-9_20} }- Yu Zi
Yun Luo
Zihao Guang
Lianyong Qi
Taoran Wu
Xuyun Zhang
Year: 2020
Anomalous Taxi Route Detection System Based on Cloud Services
CLOUDCOMP
Springer
DOI: 10.1007/978-3-030-48513-9_20
Abstract
Machine learning is very popular right now. We can apply the knowledge of machine learning to deal with some problems in our daily life. Taxi service provides a convenient way of transportation, especially for those who travel to an unfamiliar place. But there can be a risk that the passenger gets overcharged on the unnecessary mileages. To help the passenger to determine whether the taxi driver has made a detour, we propose a solution which is a cloud-based system and applies machine learning algorithms to detect anomaly taxi trajectory for the passenger. This paper briefly describes the research on several state-of-art detection methods. It also demonstrates the system architecture design in detail and gives the reader a big picture on what parts of the application have been implemented.
