Realtime Predictive Patrolling and Routing with Mobility and Emergency Calls Data

Publication Year: 2020 Publication Type : ConferenceProceeding


A well-planned patrol route plays a crucial role in increasing public security. Most of the existing studies designed the patrol route in a static manner. Situations when rerouting of patrol path are required due to the emergencies, e.g., an accident or ongoing homicide, are not considered. In this paper, we formulate the crime patrol routing problem jointly with dynamic crime event prediction, utilising crowdsourced check-in and real-time emergency call data. The extensive experiment on real-world datasets verifies the effectiveness of the proposed dynamic crime patrol route using different evaluation metrics.


    author = {Shakila Khan Rumi and Wei Shao and Flora D. Salim},
    bibsource = {dblp computer science bibliography,},
    biburl = {},
    booktitle = {Proceedings of the Fourteenth International AAAI Conference on Web and Social Media, ICWSM 2020, Held Virtually, Original Venue: Atlanta, Georgia, USA, June 8-11, 2020},
    editor = {Munmun De Choudhury and Rumi Chunara and Aron Culotta and Brooke Foucault Welles},
    pages = {964--968},
    publisher = {AAAI Press},
    timestamp = {Wed, 10 Jun 2020 09:21:45 +0200},
    title = {Realtime Predictive Patrolling and Routing with Mobility and Emergency Calls Data},
    url = {},
    year = {2020}


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