Research Article
Crime Prediction Using Big Data Analysis
@INPROCEEDINGS{10.4108/eai.7-9-2021.2314943, author={Hussam Hashim Hussein and Ahmed Talib Abdulameer}, title={Crime Prediction Using Big Data Analysis}, proceedings={Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9 September 2021, Sakarya, Turkey}, publisher={EAI}, proceedings_a={IMDC-IST}, year={2022}, month={1}, keywords={crime big data analysis deep learning machine learning recurrent neural network (rnn)/long short-term memory (lstm)}, doi={10.4108/eai.7-9-2021.2314943} }- Hussam Hashim Hussein
Ahmed Talib Abdulameer
Year: 2022
Crime Prediction Using Big Data Analysis
IMDC-IST
EAI
DOI: 10.4108/eai.7-9-2021.2314943
Abstract
Crime is one of the most dangerous phenomena around the world. It is impossible to find a country or society free of crime, where criminals use all modern techniques and advanced technological methods in committing crimes, for example, cybercrime. In recent years, the generation of raw big crime data has been increased, therefore big data analysis become mandatory. Deep Learning is employed by using (LSTM) which is one of the Recurrent Neural Network (RNN) types. 'Criminal data in Chicago' is used as a dataset. An intelligent model is proposed for type, time, and place crime prediction to address the problem of high crime rates and reaching to help (police agencies - law enforcement institutions) to predict crime, reduce the spread of crime, as well as to make the best usage of security sources of (police elements - resources).
