PREDICTING THE RATE OF CRIME USING KNN ALGORITHM. - KUMAR, DEWASHISH; KUMAR, ABHINASH; GOWRI, S.; SIVASANGARI, A.; VIMALI, J. S.; KUMARI, G. ROSLINENESA (Turkish Journal of Physiotherapy Rehabilitation, 2021)
Crime is a common societal problem that has an effect on people's personal happiness and economic growth. It is regarded as a vital factor in deciding whether or not people should migrate to another city and what places should be avoided while travelling. With the rise of violations, law enforcement agencies are requesting more advanced regional data systems and modern information mining methods to help them better investigate corruption and protect their organisations. Despite the fact that violations can occur anywhere, it is essential that when criminals are looking for opportunities to commit wrongdoing, they search in the most common places. We hope to raise people's awareness of dangerous places in different eras by providing an information mining method for determining the most criminal hotspots and discovering the type, place, and time of committed wrongdoings. As a result, our proposed arrangement could allow people to avoid certain areas at particular times while also saving lives. Getting this kind of knowledge will also assist people in making better choices on where they want to live. Police authorities, on the other hand, may use this solution to increase the degree of wrongdoing prediction and aversion. It will be beneficial for the allocation of police assets. We want to make it possible by making the bulk of this data accessible.