ItemConference Paper

An Intelligent Cognitive Framework for Crime Prediction in Smart Cities using Video Mining

Title
An Intelligent Cognitive Framework for Crime Prediction in Smart Cities using Video Mining
Creator
Joshi, Satvik; Sharma, Harshvardhan; Singh, Yajush Pratap; Ahmed, Sayed Abu Lais Ezaz; Sharma, Vandana
Description
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.
Source
2025 International Conference on Artificial Intelligence and Machine Vision, AIMV 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Action recognition; Anomaly detection; Artificial intelligence (AI); Computer vision; Crime prediction; Deep learning; Legal compliance; Object detection; Privacy; Smart cities; Video mining
Coverage
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
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833152697-9;
Format
online
Language
English
Type
Conference paper

Citation

Joshi, Satvik; Sharma, Harshvardhan; Singh, Yajush Pratap; Ahmed, Sayed Abu Lais Ezaz; Sharma, Vandana, “An Intelligent Cognitive Framework for Crime Prediction in Smart Cities using Video Mining,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25749.

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