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Mid-America Transportation Center

Spatial Attention Mechanism for Weakly Supervised Fire and Traffic Accident Scene Classification


Missouri University of Science & Technology

Principal Investigator
Zhaozheng Yin
PI Contact Information
Funding Source(s) and Amounts Provided
USDOT: $60,000
Intelligent Systems Center at MS&T: $14,798
Dept. of Computer Science at MS&T: $45,202
Total Project Cost
$ 120,000
Agency ID or Contract Number
Start Date
End Date
Brief Description of Research Project
During past ten years, on average there were near 16.5 thousands of hazardous materials (hazmat) transport incidents per year resulting in $82 millions of damages. Prompt, accurate, objective assessment on hazmat incidents is important for the first-responders to take appropriate actions timely, which will reduce the damage of hazmat incidents and protect the safety of people and environment. This multi-phase project aims to develop a method of processing and analyzing images captured by the crowdsourcing at incident scenes, which can aid the first-responders for hazmat incident assessment, decision-making and reporting. The outcome of the project will be a component of a smart safety enhancement system that improves the responsiveness and effectiveness of emergency responders and hospitals in dealing with hazardous material transportation incidents.
Describe Implementation of Research Outcomes
Impacts/Benefits of Implementation
Web Links
Modal Orientation
  • Autonomous
  • Economics
  • Safety and Human Performance
  • Systems