"Niyom Thai" represents health-centric footwear adorned with traditional Thai patterns, embodying an innovative approach to sustainable development tailored to the current needs of local communities. These shoes utilize natural materials to mitigate fatigue and integrate safety technologies, including location tracking via a mobile application and heart rate monitoring. This addresses the aspects of convenience and well-being in both daily life and travel
เนื่องจากปัจจัยผู้คนให้ความสนใจเรื่องสุขภาพมากขึ้นเเละรองเท้านับเป็นอีกหนึ่งเทรนด์สุขภาพที่กำลังได้รับความสนใจในยุคนี้ อีกทั้งผ้าไทยจัดเป็นศิลปะ ที่มีเอกลักษณ์เเละความสวยงาม คณะผู้จัดทำจึงมีเเนวคิดที่จะออกแบบลวดลายไทยให้เข้ากับยุคสมัยเเต่ยังคงความเป็นเป็นไทยและนำเทคโนโลยีมาผสมผสานเข้าด้วยกันให้เกิดนวัตกรรมรองเท้าเพื่อสุขภาพลายไทย
คณะวิศวกรรมศาสตร์
This project aims to develop an AI-powered system for detecting and classifying wall cracks using image processing. It identifies different crack types, assesses severity, and ensures accuracy across various image conditions. The goal is to support preventive maintenance by enabling early detection of structural issues, reducing repair costs, and improving safety.
คณะวิศวกรรมศาสตร์
Due to the modern urban system's high demand for stable electricity supply, underground cable power transmission has been increasingly adopted as a replacement for overhead power transmission. However, underground cable transmission still faces several operational challenges, such as significantly higher investment costs compared to overhead transmission, prolonged repair times in the event of system failures, limited fault analysis capabilities, and restricted capacity for additional load handling. This research project is designed to study the issues associated with the 22 kV XLPE underground cable system by utilizing the polarization and depolarization current analysis technique, a modern insulation diagnostic method.
คณะวิศวกรรมศาสตร์
This project has been developed to address medical challenges related to the process of counting and classifying blood cells from samples, a task that requires both time and high precision. To reduce the workload of medical personnel, the developers have created a platform and an artificial intelligence (AI) system capable of automatically classifying and counting cells from sample images. This system is designed to assist medical laboratory technicians by enabling them to work more efficiently and accurately, reducing the time required for analysis. Furthermore, it promotes the advancement of medical technology, ensuring effective usability from classrooms and laboratories to hospitals.