Efficient Neural Network model for Cyber Crime Foreca

Abstract

Depending on the gravity of the offence, a person who commits a crime faces legal repercussions from the state or other authorities, including jail time and fines. There has been an alarming rise in the number and variety of criminal acts, necessitating the creation by government agencies of effective techniques for taking preventive actions. Traditional crime-solving methods aren't cutting it in today's environment of rising crime since they're too slow and inefficient. If we can devise methods for accurately predicting crime before it occurs or create a "machine" that can aid police officers, it will relieve the pressure on law enforcement and help to reduce crime. Machine learning (ML) and computer vision techniques should be used to accomplish this. A few examples are presented in this work, and their outcomes compelled us to conduct further research in this area. As a result of these statistical insights, crime detection and prevention strategies have changed significantly. Using a mix of machine learning and computer vision, law enforcement agencies or authorities can detect, prevent, and solve crimes at a much faster and more accurate rate, according to the goal of this study. In a nutshell, machine learning and computer vision can revolutionise law enforcement.