文章基本信息

标题：A Mobile Information System Based on Crowd-Sensed and Official Crime Data for Finding Safe Routes: A Case Study of Mexico City
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作者：Félix Mata ; Miguel Torres-Ruiz ; Giovanni Guzmán 等
期刊名称：Mobile Information Systems
印刷版ISSN：1574-017X
出版年度：2016
卷号：2016
DOI：10.1155/2016/8068209
出版社：Hindawi Publishing Corporation
摘要：Mobile information systems agendas are increasingly becoming an essential part of human life and they play an important role in several daily activities. These have been developed for different contexts such as public facilities in smart cities, health care, traffic congestions, e-commerce, financial security, user-generated content, and crowdsourcing. In GIScience, problems related to routing systems have been deeply explored by using several techniques, but they are not focused on security or crime rates. In this paper, an approach to provide estimations defined by crime rates for generating safe routes in mobile devices is proposed. It consists of integrating crowd-sensed and official crime data with a mobile application. Thus, data are semantically processed by an ontology and classified by the Bayes algorithm. A geospatial repository was used to store tweets related to crime events of Mexico City and official reports that were geocoded for obtaining safe routes. A forecast related to crime events that can occur in a certain place with the collected information was performed. The novelty is a hybrid approach based on semantic processing to retrieve relevant data from unstructured data sources and a classifier algorithm to collect relevant crime data from official government reports with a mobile application.