In today’s world, the issue of harassment in public and private spaces remains a significant concern, impacting the safety and freedom of women globally. "Develop For Her - 4.0" is a technology-driven initiative aimed at addressing this pervasive issue through an innovative solution that leverages artificial intelligence and webcam technology for the real-time detection of harassment, ensuring immediate response and intervention.
Harassment is a critical problem that undermines the safety and freedom of women across the globe. The need for fast and effective responses to harassment incidents is crucial in preventing harm and providing a sense of security to those affected.
Real-Time Harassment Detection: Utilize webcam technology to detect harassment in real time.
Immediate SOS Alert Mechanism: Implement an alert system that notifies authorities instantly upon detection, facilitating prompt intervention.
Our solution is an AI-powered surveillance system designed to monitor and analyze behaviors indicative of harassment through webcam feeds. Using advanced machine learning algorithms, the system evaluates live footage for potential threats and automatically triggers an SOS signal to the designated authorities upon detection, including precise location data for swift action.
Increase in the prevention and reduction of harassment incidents through deterrence.
Improved safety for women in monitored environments.
Faster response times by authorities to harassment situations.
Video Capture: Captures video from the webcam.
Frame Processing: Processes each frame for analysis using the VGG16 model.
Feature Extraction: Utilizes the VGG16 base model for extracting features.
Harassment Detection: Predicts the presence of harassment and displays the prediction on the video frame.
Live Updates: Continuously updates the interface with the live video feed and prediction results.
Languages & Frameworks: Python, OpenCV
Tools & Libraries: TensorFlow, Pywhatkit (for WhatsApp SOS alerts), ip-api (for location coordinates), Streamlit
Architecture: Frontend (User Dashboard), Backend (Processing and Analysis, SOS Trigger Mechanism), Machine Learning Models (VGGNet16 CNN for harassment detection)
This system targets educational institutions, workplaces, public transportation systems, and public spaces where surveillance cameras are already installed, offering a scalable and practical solution for enhancing women's safety.