Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Joshi, Satvik; Sharma, Harshvardhan; Singh, Yajush Pratap; Ahmed, Sayed Abu Lais Ezaz; Sharma, Vandana Title A name given to the resource An Intelligent Cognitive Framework for Crime Prediction in Smart Cities using Video Mining Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Artificial Intelligence and Machine Vision, AIMV 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AIMV66517.2025.11203581" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIMV66517.2025.11203581</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105021819749?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105021819749?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Joshi S., Kalinga Institute of Industrial Technology, School of Computer Engineering, Bhubaneswar, India; Sharma H., Kalinga Institute of Industrial Technology, School of Computer Engineering, Bhubaneswar, India; Singh Y.P., IIT Patna, Department of Computer Science and Engineering, India; Ahmed S.A.L.E., Chandigarh University, Department of Computer Science and Engineering, Punjab, India; Sharma V., CHRIST University, Computer Science Department, Bengaluru, India Description An account of the resource Booming development in cities with dense population have led to urban policing and public safety emerging as urgent concerns in city environments.current monitoring practices including CCTV'S and other IOT sensors generate a vast amount of data ,thus making them inadequate for the task. However a combination of video mining,computer vision,artificial intelligence and data mining techniques,do offer us a better framework for monitoring and real-time detection of crime in Smart city"s environment. This paper proposes an intelligent and Cognitive framework for prediction of crime. by combining various advanced modals such as YOLO (You took Only Look Once) for detecting objects, 3D Convolutional Neural Networks (CNN) for recognizing actions, deep SORT for tracking multiple objects, One-class SVM for detecting anomaly and LSTM for behavioral analysis. These modals can organized to function in a coherent system which can be organized to distinguish examine and trail illegal activities such of mugging, robbery, pick pocketing, violence, utilizing available live video feeds. By efficient date processing, and overcoming shortcomings such of limited labeled datasets and real-time feed detection, this framework can provide practical conclusion making tool for law enforcement in urban smart city environments which can enhance urban safety.Besides effective crime detection,this tool compiles with established ethical standards such as upholding privacy and legal compliance. 2025 IEEE. Subject The topic of the resource Action recognition; Anomaly detection; Artificial intelligence (AI); Computer vision; Crime prediction; Deep learning; Legal compliance; Object detection; Privacy; Smart cities; Video mining Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152697-9; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online