International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Ensuring the safety of women has become an urgent issue in contemporary society, as instances of harassment, abuse, and violence continue to appear in both physical and virtual spaces. Despite increasing awareness and evolving legal frameworks, many cases remain unreported due to fear, embarrassment, or a lack of accessible and reliable support systems. Mahila Suraksha Nyayavani is an intelligent web-based application developed to provide a secure and confidential environment for women to report incidents safely.

The system incorporates a Natural Language Processing (NLP) model built on BERT (Bidirectional Encoder Representations from Transformers) to automatically interpret and classify reports based on their level of urgency and potential risk. Critical cases are prioritized for faster response and intervention by concerned authorities. In addition to its reporting function, the platform emphasizes awareness and empowerment through categorized articles, self-defense tutorials, and real-life case studies.

It also includes a chatbot interface that provides instant assistance, step-by-step guidance, and legal information. By integrating AI-based risk evaluation, digital awareness, and institutional collaboration, Mahila Suraksha Nyayavani acts as a holistic safety and education platform, strengthening both prevention and response mechanisms for women’s security.

Keywords: Women Safety, Crime Reporting, NLP, Sentiment Analysis, Deep Learning, BERT, Risk Prediction, Web Application.

Downloads: | DOI: 10.17148/IJARCCE.2025.141295