@article{MAKHILLJEAS201914217355,
    title = {Investigation on the Use of Graph Signal Processing for an Intelligent Taxis
Transportation System to Study Human Activites},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {2},
    pages = {526-533},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.526.533},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.526.533},
    author = {Ali Khalaf Nawar and},
    keywords = {Graph signal processing,analysis huge data,an intelligent taxis transportation system,multiplesource,dynamic data,transportation activities},
    abstract = {This study demonstrates the benefits of using Graph Signal Processing (GSP) techniques for an
intelligent taxis transportation system. Graph signal processing, an application arising to handle multiple source
signals on a graph, has developed into an active field of research during the last several years due to its ability
to analyze enormous datasets or dynamic data that usually pose a challenge to researchers. We introduce a
possible method of using graph signal processing and its operations to analyze signals in a network of taxi
stand locations where the taxis can be sensors for human activities. An example is given using real data of taxi’s
and stand’s locations in San Francisco where the number of taxis around these stands is the detected signal.
The results showed the effectiveness of using graph Fourier transform to detect the anomalies in the signals
which represent unusual transportation activities for human or driver distributions within the taxi network.}
    }