Korea University of Technology and Education announced on the 4th that it is holding on campus through the 5th the ‘2026 Academic Year 32nd Graduation Research Works Exhibition (Intensive Semester System)’.

The Graduation Research Works Exhibition is a flagship engineering education program of Korea University of Technology and Education in which third- and fourth-year students directly design and produce works that can be applied to industrial sites based on their major knowledge and practical skills.

The exhibition this year features a total of 148 research works, including 40 outstanding projects selected through screening by each major from the School of Mechanical Engineering, the School of Electrical, Electronic and Communications Engineering, the School of Computer Engineering, the Department of Design Engineering, the Department of Architectural Engineering, and the Department of Energy and Advanced Materials Engineering.

A defining feature of this exhibition is that artificial intelligence (AI) and robot technologies go beyond simple technological implementation to focus on solving problems in industrial settings and everyday life. Whereas last year dealt with advanced technologies such as robots, drones, artificial intelligence, eco-friendliness, and smart farms, this year many entries aimed at practical social and industrial problem solving were submitted, including fraud prevention, emergency medicine, industrial safety, construction-site monitoring, support for people with visual impairments, and smart-farm safety management.

A team of three, including Lee Jun-young from the School of Computer Engineering, developed the ‘ScamGuard: A data-proven fraud risk analysis platform’. This service has AI analyze various types of materials such as text messages, KakaoTalk captures, images, and voice conversations to determine the likelihood of fraud and provide a risk level. It drew attention as a work that can help prevent harm amid increasingly sophisticated voice phishing and online scams.

In Architectural Engineering, research on optimizing path planning for construction-site monitoring using a quadruped robot and on the applicability of non-load-bearing bricks made from spent coffee grounds attracted interest.

In Energy and Advanced Materials Engineering, results were showcased in the eco-friendly and energy efficiency fields, including a hydrogen sulfide gas sensor for smart-farm safety monitoring, an energy-saving smart farm, and a copper-based reversible metal deposition smart window.