Crime Forecasting Using Historical Crime Location Using CNN-Based Images Classification Mechanism

Crime Forecasting Using Historical Crime Location Using CNN-Based Images Classification Mechanism

Vishnu Venkatesh N., Priyank Singhal, Digvijay Pandey, Meenakshi Sharma, Rupal Rautdesai, Deepti Nahush Khubalkar, Ankur Gupta
Copyright: © 2023 |Pages: 16
DOI: 10.4018/978-1-6684-8618-4.ch013
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Abstract

The present research is focused on crime forecasting and CNN has been used for image classification in order to categorize crime events. However, there are different classification mechanisms used in conventional research work. But CNN is playing a significant role in identification and prediction of crime. The major issues during CNN based classification are time consumption and accuracy. However, proposed research has resolved issue of time consumption by reducing image size by applying the RGB2GRAY model, and images are resized before training operation. Simulation results conclude that the proposed work provides a scalable and reliable approach for crime forecasting.
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1. Introduction

1.1 Crime Forecasting

Predicting the likelihood of drug offences, burglaries, and other crimes based on past trends in a neighborhood or community may help with crime prevention and the allocation of resources. For a long time, the FBI's annual reports have been the gold standard for crime prediction (Babu, S.Z.D., et al, 2022). These figures only provide a snapshot of the national crime problem annually or even daily. Local communities can better deal with criminal activities and police outreach if police personnel and departments are able to keep tabs on crime trends and police response strategies. In order to keep more citizens safe in their communities, law enforcement agencies may benefit from centralized crime forecasting methodologies and internet data that is regularly updated (Bansal R., 2021).

By seeing the patterns that emerge in other cities, towns, and regions, those in transition may better prepare for the challenges that lie ahead. Police actions and reactions are also monitored in crime prediction (Boukabous, M., 2023). This method would lead to more standardised record keeping, even though the things monitored now differ from department to department. Predicting the occurrence of a crime may assist authorities keep tabs on how long it takes police to get on the scene, what kind of force is used, whether or not anybody is shot, how many people are injured, and how quickly emergency medical services respond (Dakalbab, F., et al, 2022). It might also help authorities determine if they need to revise their rules or give further training to their officers in order to improve their relationships with the people they serve. (Dushyant, K., et al, 2022)

1.2 Benefits of Crime Forecasting

In regions where a pattern can be found for early warnings to protect others from being victimised, crime forecasting may help lower the occurrence of violent crime (Esquivel, N., 2020). When police officers are experiencing trouble communicating with members of the community, these internal quality control measures may assist ensure that no lives are lost due to an error. (Fan, Y., 2021) Forecasting criminal activity also facilitates collaboration between law enforcement and educational institutions, which in turn improves both the quality and quantity of crime-prevention research and training. In an effort to effectively police their communities and use less force, researchers in the field of criminal justice are always developing new methods to improve police work (Fan, Y., 2021). Predicting where crimes will occur may help a community allocate resources more effectively, allowing the police to protect (Gupta A. et al, 2019) the most at-risk neighborhoods?

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