dc.contributor.authorHe, Kelvin Zhenhao
dc.date.accessioned2014-04-23T12:06:10Z
dc.date.available2014-04-23T12:06:10Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10356/59130
dc.description.abstractThe need of detection of patterns and behaviors has been increasing in demand in the recent years as the quantity of moving objects rises. Examples of moving objects can be vehicles, human beings, animals or even vessels. By acquiring the positions of moving objects and analyzing them, we can find out the behaviors of the subjects (moving objects). Any behavior that deviates from the normal pattern can be used to interpret as urgent or even important to the subject. There are existing sources, reports on the geometric attributes of the positions, trajectories of moving objects; however the other important properties such as the semantics and the background geographical information are often left out. The objective of this FYP is to design and implement a program to do detection of patterns and moving objects anomalies from historical logs. The program will take in files containing geometric attributes of a human being and converting the data into a file that can be displayed onto Google Earth. Based on the current geometric position of the subject and the historical logs of previous travels, the program can detect any abnormal patterns and behaviors made by the subject.en_US
dc.format.extent22 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineering::Mathematics of computing::Numerical analysisen_US
dc.titleDetecting anomalies in large number of moving objectsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorHsu Wen Jingen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US


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