Crime Prediction and Prevention Using Design Intervention and Artificial Intelligence

Abstract

One of the most important concerns facing society is crime prevention. The rate of crime is sharply rising in spite of the implementation of numerous measures. As of 2023, the total number of crimes reported in India is 445.9 per 100,000 citizens. Moreover, it has been found that the most common type of crime in India is theft, with a crime rate of 42.9 incidents per lakh population. This paper proposes the use of artificial intelligence and machine learning to develop a model that predicts criminal activities. An algorithm is formulated based on logic and pattern recognition to validate the proposed solution. The method applied is design thinking that employs a holistic approach to develop an efficient crime prevention system. Human–computer interaction, an integral part of the predictive model, is utilised to address loopholes in the proposed system. The internet-of-things (IoT) is employed in this study to enable connectivity and communication, while artificial intelligence (AI) is utilised to optimise system performance. Model validation is carried out by developing a python code and designing the interface screens. Furthermore, this predictive model is applied in a home security device. It can thus be seen that the algorithm and the system are flexible for various applications based on different needs and will in turn help in the reduction of criminal activities, ensuring the creation of a safe society. The future scope indicated involves improving the model by using data from different types of crimes and regions.