SAFEZONE: AI-Powered Web Application for Safety, Legal Support and Emergency Assistance

Abstract

SafeZone is an AI-based web safety platform designed to provide support and protection for everyone. It uses modern web technologies and AI to create a secure space where users can record incidents, report abuse anonymously, and connect with a supportive community. The platform includes an Incident Recording Vault to safely store evidence, an Anonymous Abuse Reporting and Support System for confidential help, and a Social Community Page where users can share experiences and spread awareness. SafeZone offers secure login using JWT with role-based access for Admin and User, and manages data efficiently using MongoDB Atlas. Overall, SafeZone aims to create a secure, inclusive, and safe online environment for all users.

Introduction

The text presents SafeZone, an AI-powered digital safety and support application designed to address growing concerns related to personal safety, harassment, abuse, and false accusations. Many individuals hesitate to seek help due to fear, social stigma, or lack of resources, and SafeZone aims to overcome these barriers by offering a secure, anonymous, and all-in-one safety solution using Artificial Intelligence, cloud computing, encryption, and real-time communication.

The system consists of six intelligent modules: AI-based threat detection and SOS alerts, an encrypted incident recording vault, an anonymous social support community, a false accusation analyzer, anonymous abuse reporting, and an emergency audio-video recorder. Together, these modules provide proactive threat detection, secure evidence storage, anonymous reporting, emotional support, and reliable emergency response.

SafeZone works by continuously monitoring sound and motion to detect danger and automatically trigger SOS alerts with live location sharing. Evidence such as audio, video, images, and location data is securely captured and stored using AES encryption, while user authentication is handled through JWT for security. Privacy is ensured through anonymous, end-to-end encrypted communication. An AI-based analyzer verifies the authenticity of digital evidence by examining metadata and timestamps to reduce false accusations.

The system follows a cloud-based deployment with a React frontend, Node.js/Express backend, and MongoDB Atlas for secure data storage. It includes user and admin roles, supports anonymous interaction, and provides a user-friendly interface for emergency actions, evidence management, and community support. Overall, SafeZone establishes a comprehensive, secure, and intelligent personal safety platform that enhances user confidence, privacy, and protection in critical situations.

Conclusion

The SafeZone system shows how a proactive and intelligent approach can improve personal safety and support. By using AI-based threat detection, automatic SOS alerts, and secure evidence recording, the system helps users during emergencies effectively. Features like encrypted cloud storage and anonymous reporting increase user trust and privacy. This project proves that applications like SafeZone are very useful for ensuring safety, support, and justice in today’s digital world.

References

[1] Ian Sommerville, Software Engineering, Pearson Education, 10th Edition, 2015. [2] Daniel Shiffman, Learning JavaScript: Building Interactive Applications, O’Reilly Media, 2019. [3] R. Kumar, S. Patel, “AI-Based Threat Detection and Emergency Response Systems,” International Journal of Advanced Computing and Technology, Vol. 12, No. 3, 2021. [4] L. Chen, M. Singh, “Encrypted Evidence Management and Cloud Storage Solutions,” Journal of Cyber Security and Data Protection, Vol. 8, No. 2, 2019. [5] Google Firebase Documentation, Authentication, Cloud Storage and Real-Time Database, 2023.

Copyright

Copyright © 2026 Kamatchi T P, Suganya J, Dhaarshan V, Karthick S, Praneeth S T, Akilesh M. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.