Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2025 340030 Introduction to Intelligent Railway System 1 3.0 3 ★ Luh Yuan-Ping 4ME3A
4ME3B 44 1 大三合開；限40人

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	340030	Introduction to Intelligent Railway System	1	3.0	3	★	Luh Yuan-Ping	4ME3A 4ME3B	44	1	大三合開；限40人

Course Plan：

Instructor Luh Yuan-Ping　Office Hours

Email yuan@ntut.edu.tw

Last Updated 2024-12-20 10:29:34

Course Objective 本課程為本校「智慧鐵道學程」的進階基礎課程。課程開授之目標，是希望藉由先進智慧鐵道系統的介紹，使修課學生能夠清楚瞭解鐵道產業的未來發展方向，並引領學生積極投入各種先進智慧鐵道應用系統之研究。本課程是以同時段合院授課的方式、針對選讀學程之學生、邀請智慧鐵道系統相關、學有專精的技術研發人員、以業師的身份共同參與授課。本課程會要求修課同學於期末報告時進行實作系統的展示，並邀請鐵道產業專家擔任評審。修習本課程前，不同學系之學生須先修習的課程清單另訂定之。 This course is one of the advanced core courses for the Intelligent Railway Curriculum. The aim of this course is, via the introduction of advanced intelligent rail system, to have the students realize thoroughly the development trend of futuristic rail industry, and subsequently, to encourage the students into the research and development of various application systems for intelligent railway. This course is a joint lecture among departments inside our college with synchronized class hours. The industrial instructors to our participant students include R&D experts from relevant fields in intelligent rail industry. In their term reports, the students will have to demonstrate the prototypes of their projects and to be reviewed by the invited senior professionals from rail industry. The prerequisites for taking this course will be determined based on the background of students with different majors.

Course Schedule 課程進度謹供參考：第一週課程簡介第二週工業4.0九大前瞻技術第三週工業物聯網（IIoT）第四週軟體定義一切的智慧型大眾運輸系統第五週建築資訊模型（BIM）第六週產品生命週期管理（PLM）第七週擴增實境（AR）輔助系統創新應用第八週故障診斷、預測與健康管理（PHM）系統第九週 (期中考週) 第十週先進列車控制系統（ERTMS、CBTC、PTC）第十一週整合票證與旅客服務資訊系統第十二週鐵道號誌系統第十三週 AI 驅動的鐵路演進：大模型在智慧交通中的角色第十四週結合圖神經網絡的智慧鐵道系統優化策略第十五週智慧鐵道系統中的AI Defined Networking 第十六週 PHM在現代智慧鐵道的應用與影響第十七週期末報告第十八週 (期末考週)

Evaluation and grading policy 平時作業成績：50% 出席：10% 期末報告：40% 課堂參與額外加分翹課一次扣總成績10分、請假第二次開始扣總成績1分、遲到早退一次扣總成績1分、學期缺課次數過多將增加總扣分數、作弊一律以不及格論

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
1. 自編講義 2. 軌道工程學，作者：黃漢榮，高立出版社，出版日：2016/09/01。 3. 軌道機電系統概論，作者：林仁生，高立出版社，出版日：2003/12/01。

The access to curricular consultation 711-2
分機2069

Expanding teaching and resources

The course corresponds to the SDGs 無（None）

Does the course incorporate AI

Note
上課群組(課程相關問題皆在群組裡由助教回答)

Instructor	Luh Yuan-Ping　Office Hours
Email	yuan@ntut.edu.tw
Last Updated	2024-12-20 10:29:34
Course Objective	本課程為本校「智慧鐵道學程」的進階基礎課程。課程開授之目標，是希望藉由先進智慧鐵道系統的介紹，使修課學生能夠清楚瞭解鐵道產業的未來發展方向，並引領學生積極投入各種先進智慧鐵道應用系統之研究。本課程是以同時段合院授課的方式、針對選讀學程之學生、邀請智慧鐵道系統相關、學有專精的技術研發人員、以業師的身份共同參與授課。本課程會要求修課同學於期末報告時進行實作系統的展示，並邀請鐵道產業專家擔任評審。修習本課程前，不同學系之學生須先修習的課程清單另訂定之。 This course is one of the advanced core courses for the Intelligent Railway Curriculum. The aim of this course is, via the introduction of advanced intelligent rail system, to have the students realize thoroughly the development trend of futuristic rail industry, and subsequently, to encourage the students into the research and development of various application systems for intelligent railway. This course is a joint lecture among departments inside our college with synchronized class hours. The industrial instructors to our participant students include R&D experts from relevant fields in intelligent rail industry. In their term reports, the students will have to demonstrate the prototypes of their projects and to be reviewed by the invited senior professionals from rail industry. The prerequisites for taking this course will be determined based on the background of students with different majors.
Course Schedule	課程進度謹供參考：第一週課程簡介第二週工業4.0九大前瞻技術第三週工業物聯網（IIoT）第四週軟體定義一切的智慧型大眾運輸系統第五週建築資訊模型（BIM）第六週產品生命週期管理（PLM）第七週擴增實境（AR）輔助系統創新應用第八週故障診斷、預測與健康管理（PHM）系統第九週 (期中考週) 第十週先進列車控制系統（ERTMS、CBTC、PTC）第十一週整合票證與旅客服務資訊系統第十二週鐵道號誌系統第十三週 AI 驅動的鐵路演進：大模型在智慧交通中的角色第十四週結合圖神經網絡的智慧鐵道系統優化策略第十五週智慧鐵道系統中的AI Defined Networking 第十六週 PHM在現代智慧鐵道的應用與影響第十七週期末報告第十八週 (期末考週)
Evaluation and grading policy	平時作業成績：50% 出席：10% 期末報告：40% 課堂參與額外加分翹課一次扣總成績10分、請假第二次開始扣總成績1分、遲到早退一次扣總成績1分、學期缺課次數過多將增加總扣分數、作弊一律以不及格論
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No 1. 自編講義 2. 軌道工程學，作者：黃漢榮，高立出版社，出版日：2016/09/01。 3. 軌道機電系統概論，作者：林仁生，高立出版社，出版日：2003/12/01。
The access to curricular consultation	711-2 分機2069
Expanding teaching and resources
The course corresponds to the SDGs	無（None）
Does the course incorporate AI
Note	上課群組(課程相關問題皆在群組裡由助教回答)