• Dr. Ghanshyam Parmar

Any intentional act that harms oneself or another, damages or destroys property, or causes someone else harm counts as a crime for the purposes of criminal law, depending on the severity of the offence. Law enforcement organisations must develop effective enforcement tools due to the alarming rise in the quantity and variety of illegal activity. Traditional crime-solving techniques are ineffective in the high-crime environment of today because of their sluggishness and inefficiency. If I figure up a technique to accurately predict crime before it happens, I might be able to lessen the strain for police officers and help with crime prevention. To accomplish this, I advise utilising machine learning and computer vision techniques. I discuss the outcomes of numerous instances where similar tactics were applied throughout this study, which piqued our curiosity in subsequent research. The primary justification for the change in crime prevention and prediction tactics is based on the authorities' earlier and later data observations. The main objective of this research endeavour is to determine whether machine learning and computer vision can assist law enforcement and other authorities in predicting, preventing, and solving crimes more quickly and correctly. Law enforcement organisations might change as a result of the employment of artificial intelligence and computer vision.

Computer Vision, Machine Learning, crime prediction and prevention.

"A Survey on Crime Prediction and Prevention Techniques using Computer Vision with Machine Learnin g", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.381-389, March-2019, Available :http://www.jetir.org/papers/JETIR1903O54.pdf

"A Survey on Crime Prediction and Prevention Techniques using Computer Vision with Machine Learnin g", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp381-389, March-2019, Available at : http://www.jetir.org/papers/JETIR1903O54.pdf