Crime Types and Occurrence Using Machine Learning Algorithm

S. Tamilamuthan, V. Sangeetha

2023

Abstract

This research paper explores the application of machine learning in crime analysis and prediction, emphasizing the importance of accurate crime classification and occurrence forecasting for public safety. It employs a diverse dataset containing information on crime incidents, including time, location, demographics, and historical records. Various machine learning algorithms, including decision trees, support vector machines, random forests, and neural networks, are compared to create a robust model. The study uses performance metrics such as accuracy, precision, recall, and F1 score to assess these algorithms’ effectiveness. Feature selection techniques help identify influential factors in crime determination and occurrence, aiding the development of targeted prevention strategies. The results demonstrate that machine learning is highly effective, outperforming traditional statistical methods and offering valuable insights for law enforcement agencies to focus their resources efficiently. This research underscores the potential of machine learning in enhancing crime prevention and public safety efforts.

Paper Citation

in Harvard Style

Tamilamuthan S. and Sangeetha V. (2023). Crime Types and Occurrence Using Machine Learning Algorithm. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 286-293. DOI: 10.5220/0012614500003739

in Bibtex Style

@conference{ai4iot23,
author={S. Tamilamuthan and V. Sangeetha},
title={Crime Types and Occurrence Using Machine Learning Algorithm},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={286-293},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012614500003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Crime Types and Occurrence Using Machine Learning Algorithm
SN - 978-989-758-661-3
AU - Tamilamuthan S.
AU - Sangeetha V.
PY - 2023
SP - 286
EP - 293
DO - 10.5220/0012614500003739
PB - SciTePress