AI-Powered Video Analysis for Road Sign and Infrastructure Monitoring

The client faces difficulties in efficiently monitoring highway safety features such as road signs, streetlights, and crash barriers through manual inspection of surveillance videos. Existing processes are time-consuming, prone to human error, and lack real-time insights, leading to potential safety risks and increased operational costs.

A mid-to-large transportation infrastructure management company seeking to automate the monitoring and counting of road signs, streetlights, and crash barriers from surveillance videos to ensure highway safety and maintenance efficiency.

• Develop an AI-driven system capable of analyzing surveillance videos to automatically count and identify road signage, streetlights, and length of crash barriers.
• Improve accuracy of detections and counts compared to manual methods.
• Streamline the workflow of infrastructure monitoring teams, reducing review and processing time by at least 50%.
• Enhance data quality and reporting consistency for highway safety assessments.
• Support scalability and future integration of additional infrastructure features.

• Automated detection and counting of road signs, streetlights, and crash barriers in video footage.
• Adaptive dataset review and relabeling tools to ensure training data quality and model accuracy.
• Multiple solution development approaches with clear pros and cons to facilitate flexible implementation.
• Real-time or batch processing capabilities for large volumes of video data.
• User interface for visual verification of detections and manual adjustments if needed.
• Reporting module to summarize counts, locations, and potential anomalies.

• Video surveillance data sources and storage systems
• Existing infrastructure management information systems for data input/output
• Reporting and analytics dashboards

• High accuracy with a minimum of 95% detection precision and recall
• Processing speed capable of handling real-time or near-real-time video streams
• Scalability to support increasing volume of video data
• Data security and access controls for sensitive infrastructure data
• System uptime of at least 99.5%

The implementation of this AI-based video analysis system aims to significantly improve the accuracy and efficiency of highway infrastructure monitoring, reducing manual review time by at least 50%, lowering operational costs, and enhancing highway safety through timely and reliable data. It supports scalable growth and provides the foundation for proactive infrastructure maintenance and safety assurance.