Ubiquitous Crime Prevention System (UCPS) for a Safer City

Moon, Tae-Heon; Heo, Seong‐Joo; Lee, Sang-Ho

doi:10.1016/j.proenv.2014.11.028

Cited by 12 publications

(3 citation statements)

References 2 publications

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“…However, our approach retrieves information in unstructured way by a nonspecialized system. In [15], a study of crime prevention systems with an analysis of the main web and mobile crime information systems is described. Here, the information retrieval task is collaborative; however, the authors do not use a hybrid approach which integrates social and official sources.…”

Section: Discussion About the Related Workmentioning

confidence: 99%

A Mobile Information System Based on Crowd-Sensed and Official Crime Data for Finding Safe Routes: A Case Study of Mexico City

Mata

Torres-Ruiz

Guzmán

et al. 2016

Mobile Information Systems

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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.

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Section: Discussion About the Related Workmentioning

confidence: 99%

A Mobile Information System Based on Crowd-Sensed and Official Crime Data for Finding Safe Routes: A Case Study of Mexico City

Mata

Torres-Ruiz

Guzmán

et al. 2016

Mobile Information Systems

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show abstract

“…Terdapat berbagai macam teori terkait pencegahan tindak kriminal, bermula dari defensible space theory, routine activities theory, situational crime prevention theory, hingga Crime Prevention Through Enviromental Design (CPTED) [7]. Setidaknya terdapat empat prinsip utama dalam mencegah tindak kriminal dan meningkatkan rasa aman teritorial, pengamatan alami, activity support, dan kontrol akan akses (Carter et al, 2013).…”

Section: Pendahuluanunclassified

Analisis Tingkat Keamanan Ruang Terbuka Hijau Berdasarkan Variabel Keruangan Dan Fisik Taman: Studi Kasus Kota Surabaya

Danurja,

Zulkaidi,

Effendi

2024

Jurnal Penataan Ruang

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“…Analysis of the similar crime data Data collection not available and no concern with solving processing time [3,14,15,17,18,24,25,31,33,34] Clustering Data groupings into similarities and clusters Produces unreliable results with noisy data and when number of clusters are small. [11,16,17,18,19,23,25,27,36,37,38,42,43,45]…”

Section: Statistical Basedmentioning

confidence: 99%

Systematic Literature Review of Crime Prediction and Data Mining

Falade¹,

Azeta²,

Oni³

et al. 2019

RCES

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Crime is a social menace that impacts negatively on social economic development of a nation. Crime has been in existence from time immemorial and violent crime is the main enemy of the society. One of the primary responsibilities of any government is security of life and properties which translates to reduction of crime rate and provisioning of adequate security to its citizenry. To this end, government must wake up to its responsibilities by reducing crime rate and provide adequate security to its citizenry through effective, efficient and proactive policing. Any research in this direction that can help in analyzing and predicting the future occurrence of violent crime by using crime dataset is laudable. Predicting future occurrence of crime from crime dataset is well reported in literature, therefore it has become imperative to come up with an overview of the present state of the art on crime prediction and control. The systematic review present in this study focuses on crime prediction and data mining as well as the techniques employed in the past studies. The existing work is classified and grouped into different categories and are presented by using visualization approach. It is found that more studies adopted supervised learning approaches to crime prediction and control compared to other methods. The challenges encountered were also reported. Crime prediction has become hot research area in recent time because of its intending benefits to socio-economic development of a nation.

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Ubiquitous Crime Prevention System (UCPS) for a Safer City

Cited by 12 publications

References 2 publications

A Mobile Information System Based on Crowd-Sensed and Official Crime Data for Finding Safe Routes: A Case Study of Mexico City

A Mobile Information System Based on Crowd-Sensed and Official Crime Data for Finding Safe Routes: A Case Study of Mexico City

Analisis Tingkat Keamanan Ruang Terbuka Hijau Berdasarkan Variabel Keruangan Dan Fisik Taman: Studi Kasus Kota Surabaya

Systematic Literature Review of Crime Prediction and Data Mining

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