Deeprom Somkiadcharoen. Data exploration and anomaly detection on road network with unsupervised outlier detection on large-scale taxis GPS data assisting with social data. Master's Degree(Information and Communication Technology for Embedded Systems). Thammasat University. Thammasat University Library. : Thammasat University, 2016.
Data exploration and anomaly detection on road network with unsupervised outlier detection on large-scale taxis GPS data assisting with social data
Abstract:
Flows of traffic on road are a complex phenomenon. Even a small event can cause massive change on road network as cars can alter their paths or dramatically drop in overall speed. Traffic anomalies can be caused by various factors, for example, accidents, control, protests, sport events, celebrations, and natural disasters. However, as drivers on the road, we cannot know what cause the change in traffic. Thus, we called this anomaly on road network. With advancement in mobile computing and social networking services, and cheaper internet service, data are flooded from various kinds of sensors and user generated data. Combining two or more data sources to confirm to one another would yield significant results. Anomaly detection on taxi mobility data and inferring its cause from Twitter can demonstrate how can we combined sensors and social data to gain information. As a result, we tested our anomaly and inferring method on a Muang Thong Thani area. We are able to detect anomalies on the road and infer their causes via Twiiter. From 20 alerted anomalies, we are able to infer 16 of their causes from hashtags. Two of the anomalies are found from cleaned twitter data. We have one false anomaly and the last one we can confirmed on the Twitter website
Thammasat University. Thammasat University Library