University of New Mexico Leads Innovative Research on Small Railroad Safety

The University of New Mexico is spearheading research to enhance small railroad safety and maintenance. Rail CREST, backed by a $6.8M CRISI grant, will launch this fall with ten collaborative projects. This was reported by the railway transport news portal Railway Supply.

University of New Mexico Develops Cost-Effective Railroad Safety Solutions

This initiative, known as the Rail Center for Research Enhancing Short Line Transportation, will focus on railroad safety. It will bring together universities and railroads to develop advanced safety and maintenance solutions.

Partnering institutions include Penn State, Auburn University, the University of South Carolina, and Kansas State University. These universities will contribute expertise in engineering, artificial intelligence, and infrastructure maintenance.

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Researchers will assist small railroad companies in improving operations with AI, AR, and cost-effective sensors. These solutions will provide efficient, scalable, and affordable tools for infrastructure monitoring and repair.

Fernando Moreu, an associate professor at UNM, will lead his institution’s involvement in the project. He brings years of expertise in railroad bridge maintenance and infrastructure management.

Moreu emphasizes that early detection of track issues significantly reduces maintenance costs and improves safety. His team aims to make cutting-edge technologies accessible to smaller railroads.

Class One railroads already leverage AI, but they possess far greater financial resources. This project aims to bridge the gap by bringing AI solutions to smaller rail operations.

Moreu notes that large railroads collect millions of data points, enabling AI-driven decision-making. However, small railroad companies lack similar data collection capabilities.

How University of New Mexico Integrates AI and AR in Railroad Research?

UNM’s research explores using Low-cost Efficient Wireless Intelligent Sensors (LEWIS) to streamline track maintenance. These compact sensors can be mounted on trains to detect vibrations and flag potential problems.

LEWIS sensors cost approximately $50 each and provide real-time data on track conditions. They allow railroad operators to identify maintenance needs before significant issues arise.

Neuromorphic cameras, another technology under investigation, offer advanced capabilities for railroad inspections. These cameras, costing around $7,000, can integrate AI for enhanced predictive analysis.

By analyzing track images, AI-powered neuromorphic cameras can predict necessary repairs before failures occur. This predictive approach reduces downtime and prevents hazardous accidents.

Ali Mohammadkhorasani, a Ph.D. candidate at UNM, is examining how AI and AR can improve track inspections. His research aims to make assessments more accurate and reliable.

Collaborating with Penn State and industry professionals, the research team is developing augmented reality tools. These tools will help inspectors visualize structural issues more effectively.

With AR integration, inspectors can see hidden track defects that might otherwise go unnoticed. This advancement will lead to more consistent and thorough railroad safety evaluations.

The project’s ultimate goal is to modernize small railroad safety while minimizing costs. By leveraging AI and AR, researchers seek to enhance efficiency in infrastructure management.

Rail CREST’s collaborative approach unites academia and industry to drive technological innovation. The partnership enables real-world testing and refinement of safety solutions.

The research also underscores the importance of cost-effective technology in infrastructure management. Small railroads operate with limited budgets, making affordable solutions essential.

By making AI-driven tools accessible, the project empowers smaller rail companies to compete with industry leaders. This technological shift will enhance efficiency and safety across the sector.

As Rail CREST launches, researchers will continue refining their methods through extensive field testing. Their findings will shape future innovations in small railroad maintenance.

Ultimately, this initiative demonstrates how universities and industry leaders can collaborate to improve public infrastructure. With advanced technologies, small railroads can operate more safely and efficiently.

Source: www.railway-technology.com

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