Aiming at the problem that traditional method of unlicensed taxis manual check is not only timeconsuming but also inefficient

a novel automatic unlicensed taxis detection method is proposed. Vehicles refueling data of Xinjiang Province collected by Internet of things（ IOT） are analyzed on Hadoop platform. Spatial features and temporal features of vehicles refueling are extracted. Random forest algorithm is applied in research on relationship between vehicles

drivers and gas stations to discover unlicensed taxis with abnormal refueling patterns. Experiments on real-world large-scale dataset show that the proposed method has high accuracy in detecting unlicensed taxis

and its application can help relevant department improve the efficiency of unlicensed taxis detection.