PedSense: Smart Alert System for Pedestrian Safety

Description:

PedSense integrates computer vision, radar, and acoustic sensors with deep learning algorithms to continuously monitor road and rail crossings, detect hazards, and forecast pedestrian and vehicle movements. It delivers multi-modal alerts via visual, audio, and haptic signals to protect pedestrians, including people with disabilities, while prioritizing deployment in underserved communities. The modular system supports edge computing for privacy-conscious, efficient data processing and is scalable for diverse environments and future upgrades.

Key Advantages:

• Real-time multi-modal hazard detection combining cameras, radar, and acoustic sensors.
• AI-driven predictive modeling to anticipate conflicts before they occur.
• Inclusive alert system with visual, audio, and haptic notifications.
• Focus on equity through deployment in underserved communities.
• Modular, scalable, and cost-effective installation and maintenance.
• Edge computing ensures privacy and efficient data handling.
• Market-ready solution with strong commercialization potential.

Problems Solved:

• Limitations of traditional pedestrian safety measures at crossings.
• Delayed or ineffective hazard detection in low-light or obstructed conditions.
• Lack of predictive insight to prevent accidents before they happen.
• Accessibility barriers for individuals with disabilities.
• High installation and maintenance costs of existing safety systems.
• Privacy concerns related to data collected at crossings.

Market Applications:

• Traffic management companies improving pedestrian safety infrastructure.
• Smart city vendors integrating advanced safety systems.
• Municipalities targeting underserved areas for equitable safety upgrades.
• Railroad and road crossing authorities aiming to reduce accidents.
• Disability advocacy groups seeking accessible pedestrian alerts.
• Urban planners looking for scalable and adaptable safety solutions.