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Crimes against women have become a global problem, and many governments are striving to curb them. The National Crime Records Bureau indicates that crimes against women have risen substantially. In June, NCW received the most crime complaints against women in eight months. The Indian government is interested in finding a solution to this problem and promoting social progress. Each year, crime reports generate a vast amount of data, which is collated. This information may help us evaluate and anticipate criminal behavior and reduce criminal activity. Data analysis involves assessing, cleansing, manipulating, and modelling data to draw conclusions and enhance decision-making. This research uses supervision learning to analyze the Indian women's criminal examination. The police department received crime reports. Anomalies, invalid locations, longitudes, and scopes were created in advance. The study was meant to breakdown women's crimes by kind and district and produce crime heat maps. The results help decision makers predict and prevent crimes against women. Applying Find the geographical criminal hotspot and the kind of crime, such as murder, rape, sexual assault, beating, dowry threats by the husband or his family, immoral trafficking, stalking, etc.

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In current period, broken bones is a typical problem in normal human happens because of high weight is applied on bone or basic mishap and furthermore because of cancer of bone and osteoporosis. So, the exact determination of bone crack is significant viewpoints in therapeutic arena. From this research X-beam/CT pictures are utilized for object crack analysis. The picture handling systems are helpful for some applications, for example, science, security, satellite symbolism, individual photograph, medicine, etc. The techniques of picture handling, for example, picture upgrade, picture division and highlight extraction are utilized for crack recognition system. This paper utilizes canny edge location strategy for segmentation. Canny strategy produces ideal data from the bone picture. The principle point of this examination is to recognize human lower leg bone crack from X-Ray images. The tests we lead show that the proposed framework is precise and ef?cient.