An Automated Women Safety Framework Using Machine Learning and Real-Time Risk Assessment

Key Points

• The aim is to assess how machine learning can enhance safety measures for women through real-time risk assessments.
• Developed an automated framework incorporating machine learning techniques.
• Evaluated real-time risk assessment features.
• Assessed safety framework effectiveness through simulations.
• The framework shows potential for real-time risk identification.
• Participants reported increased awareness of safety issues.
• Enhanced safety interventions were noted in simulated environments.