USC Facilities Intern Develops AI-Powered Innovation for Campus Operations

University of South Carolina alumnus Michael Carson has transitioned a senior capstone project into a professional internship focused on integrating artificial intelligence into the university’s facilities management operations. By partnering with the Molinaroli College of Engineering and Computing, USC Facilities is leveraging AI to synthesize vast amounts of maintenance data, reducing report generation time from hours to seconds. This initiative highlights the growing intersection of computer science and facilities management, offering a blueprint for how institutions can use internal talent to drive operational efficiency and predictive maintenance.

Michael Carson, a computer science graduate from the University of South Carolina, collaborated with classmates Tony Lin, Julius Parker, Stephen Spear, and Lance Kimani to bridge the gap between IT and facilities management. The team was tasked with integrating AI into the university’s computerized maintenance management system (CMMS) to streamline reporting and extract actionable insights. Previously, facilities managers spent significant time manually compiling data on completed work and daily emergencies; the new AI platform synthesizes this information in approximately 60 seconds, a task that formerly required an hour of manual labor.

The AI-driven system provides USC Facilities with the ability to identify specific buildings generating the highest volume of maintenance requests and pinpoint recurring equipment failures. By uncovering these trends, the platform recommends preventative maintenance strategies and identifies potential causes of system malfunctions. Since transitioning to a paid internship, Carson has further enhanced the tool by implementing an AI-powered chatbot. This interface allows staff to query existing maintenance records using natural language, making historical data more accessible for daily decision-making.

Looking toward future applications, USC Facilities is exploring the correlation between historical maintenance records and environmental factors like weather to better understand external influences on campus operations. The department currently manages over 560,000 building automation data points and aims to apply AI toward construction insights, fault detection, and energy analysis. According to department representative Schiff, the project underscores the technical complexity of modern facilities management and the value of cross-departmental partnerships in fostering innovation and improving institutional planning.