Personal mobility pattern mining and anomaly detection in the GPS era

Abstract

Suffering from Alzheimer’s disease has become one of the critical health issues today. If an abnormal time–space pattern of such patients can be detected earlier, it will help the families to prevent some dangerous situations in advance. We have proposed a method in this study to uncover personal mobility patterns and detect abnormal behavior patterns from mobility data obtained with global position system (GPS). Experimental results showed that our proposed method is far better than other alternatives available. This proposed approach may thus render great assistance in identifying abnormal behavior, thus providing critical remedy actions in advance in this GPS era.

Keywords:

• Mobility pattern
• pattern mining
• similarity measurement
• GPS
• anomaly detection

Additional information

Funding

Part of this research was supported by the National Science Council, Taiwan, under [Grant NSC 101-2410-H-224-004].