Intellibridge: AI-Powered Precision In Bridge Maintenance Optimization[IBT-ABC-UTC-2024-C2-FAMU02]: This project will develop an intelligent system called IntelliBridge to transform the way to plan bridge maintenance. The proposed system makes use of advanced machine learning (ML) algorithms that predict the future state of bridge elements, perform cost analysis and give the best maintenance interventions that are under budget, and identify any inefficiencies in the existing strategies. Utilizing historical data from the National Bridge Inventory (NBI) and National Bridge Elements (NBE), IntelliBridge will enable actionable insights that support data-driven decision-making to deliver concerted maintenance interventions that are cost-effective, timely, and performance-driven.
1st-Cycle Projects (2024-grant)
Sociotechnical Needs Assessment and Knowledge Base Development Towards Developing a Comprehensive, Human-Centered, Risk-Based Decision Support System for Prioritizing Bridge Projects [IBT-ABC-UTC-2024-C1-FAMU01]: The objectives of this research include Create a secure, unified, integrated, and accessible geospatial knowledge base that includes heterogeneous sociotechnical data on demographics, socioeconomics, traffic, environment, and infrastructure, which will be available for prioritizing, implementing and validating bridge technologies. Develop a cloud based platform to provide access to these infrastructure, population, environment, mobility and related geographic information systems (GIS) datasets in the State of Florida. Conduct a needs assessment using data-driven approaches towards prioritizing bridge technologies. Identify the data requirements for the development of the proposed decision-making tool.
