Year: 2025
Type: article
Abstract: This project presents a Real-Time Monitoring System aimed at enhancing women’s privacy and security in gender-sensitive areas, such as female-only restrooms, changing rooms, and similar spaces. The system integrates computer vision and deep learning techniques to detect unauthorized male entry and trigger immediate alerts. Using Raspberry Pi with a Webcam, real-time video frames are processed to identify gender through a lightweight Deep Learning model. Upon detecting an unauthorized male presence, an automated notification system sends alerts to security personnel. The solution offers scalability, low-cost implementation, and easy integration with existing security infrastructures. Our approach ensures enhanced privacy and security while maintaining operational efficiency.
Authors: Pratima Prakash Sawant, Anushka Prakash Shelar, Sakshi Sachin Shelke, Yash Mohan Shete, Dr. Umakant Butkar
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410076451