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1 Title of the Article AI-Powered Anonymous Crime Reporting System with Automated Risk Assessment
2 Author's name Shilpa R: Assistant Professor, Department of Computer Science & Engineering, Sri Dharmasthala Manjunatheshwara Institute of Technology, Ujire, Karnataka, India
3 Author's name Abhisheka C Hegde, Anushree Joshi, Chinmay Naik, Darshan Hegde
4 Subject Computer Science
5 Keyword(s) Anonymous Crime Reporting, Artificial Intelligence, Machine Learning, Natural Language Processing, Privacy Protection
6 Abstract

Many crimes aren't reported-even though speaking up helps keep communities safe. Fear of being exposed keeps people quiet, along with doubts about law enforcement’s reliability. Old-style methods usually demand ID or face-to-face talk, making it harder for victims to act. These processes tend to be slow, paper-heavy, and out of touch. As tech becomes more common in daily life, better tools are needed - ones that ensure secrecy without sacrificing ease. A smarter way would let users share info privately, quickly, through trusted digital path. This project introduces a smart tool for reporting crimes, using AI to sort incidents, pull out key details, spot emotions in reports, plus judge potential dangers. It lets people share info without giving names, safely manage photos or videos, send instant warnings when danger’s high, also offers live-updating screens for police use. With features that protect user identity while delivering sharp insights, the setup tries making it easier to report issues, speed up reactions, yet build a stronger, more reliable way to handle crime.

7 Publisher Innovative Research Publication
8 Journal Name; vol., no. International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-14 Issue-1
9 Publication Date January 2026
10 Type Peer-reviewed Article
11 Format PDF
12 Uniform Resource Identifier https://ijircst.org/view_abstract.php?title=AI-Powered-Anonymous-Crime-Reporting-System-with-Automated-Risk-Assessment&year=2026&vol=14&primary=QVJULTE0MzU=
13 Digital Object Identifier(DOI) 10.55524/ijircst.2026.14.1.7   https://doi.org/10.55524/ijircst.2026.14.1.7
14 Language English
15 Page No 55-62

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