Abstract

Dubai’s crime rate appears to be significantly lower. However, do not let this lull you into a false sense of security. Most of the crime occurs in areas populated primarily by lower-income, temporary laborers originating from other countries. Most crimes attributed to this group consist of petty theft, public offenses (e.g., fighting, public intoxication, and property damage), sexual harassment, and rare incidents of violent assault. Using advanced techniques to classify which category the crime belongs to; it will help the concerned authorities to tackle the major crime happening in the City and helpful to find out rare crimes in the city. The technique will be useful for Dubai Expo 2020 events security. The purpose of this research is to analyze Dubai crime related data to reduce the crime rate in the city. The Dubai government works hard in having major events such as the Dubai World Cup (horse race) and Burj Khalifa, New Year celebration. Therefore, since Dubai had several events held previously, the previous crime data will be beneficial to be used in planning prevention strategy for EXPO 2020. This will help the authority to identify crimes in such massive gatherings by analyzing different features of the data available. The study will be helpful to find out what kind of Crimes most happened in the Past, such as Administrative Crime, High-Tech Crime, Immigration Crime, Organized Crime, Property Crime, Public Order Crime, Violent Crime. Machine learning algorithms such as random forest, SVM, and Decision tree will be used in this study to design a predictive model that Classifies a Crime with the highest accuracy.

Publication Date

5-2021

Document Type

Master's Project

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Ehsan Warriach

Campus

RIT Dubai

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