WSS21201 Special Lecture on Data-Driven Smart Systems

Hiroshima University Syllabus

Japanese

Academic Year 2024Year School/Graduate School Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Smart Innovation Program

Lecture Code WSS21201 Subject Classification Specialized Education

Subject Name データ駆動型スマートシステム特別講義

Subject Name
（Katakana）データクドウガタスマートシステムトクベツコウギ

Subject Name in
English Special Lecture on Data-Driven Smart Systems

Instructor See the class timetable.

Instructor
(Katakana) ジュギョウジカンワリヲサンショウ

Campus Higashi-Hiroshima Semester/Term 1st-Year, First Semester, 2Term

Days, Periods, and Classrooms (2T) Inte

Lesson Style Lecture Lesson Style
(More Details) 　

Lecture

Credits 2.0 Class Hours/Week 　 Language of Instruction J : Japanese

Course Level 6 : Graduate Advanced

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 11 : Electrical, Systems, and Control Engineering

Eligible Students

Keywords Model-based development (MBD), artificial intelligence, neural networks

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students)
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students)

Class Objectives
/Class Outline This lecture will be divided into two main parts.
[1] Model-based development (MBD) in the application of control technology to products.
[2] Basic concepts and industrial applications of artificial intelligence.

Class Schedule [1] (7.5 frames)
Although the automotive industry is increasingly trying to develop in line with the MBSE (Model-Based Systems Engineering) approach, the more mature components are lagging behind when it comes to the introduction of control technology. On the other hand, as with other products such as smartphones, upgrading the control technology that forms the backbone is considered essential to improve performance through software upgrades.
In this lecture.
(1) Problems in the introduction of control technology into vehicle development.
(2) 'Functional distribution' utilised to overcome this.
(3) Examples of improved control technology.
The lecture will cover the following topics.
[2] (7.5 frames)
Artificial Intelligence (AI) is a discipline that is currently advancing at an ever-increasing pace. Although today's computers have very high processing speeds, they are not as flexible as humans. Artificial Intelligence aims to turn them into "great wits". One of the directions in this direction is to realize computers that can recognise and understand events in the external world, understand natural language and respond to them, just like humans, without the need to create computers and program that can respond flexibly.
The aim of this lecture is to introduce the basic concepts of artificial intelligence, pattern understanding systems and problem solving systems for the realization of intelligent robots, with the aim of acquiring basic knowledge of the fundamentals of neurocomputers and the realization of autonomous driving of cars and intelligent robots.

Evaluation is mainly based on reports.

Text/Reference
Books,etc. Textbooks will be announced on a bulletin board later.

PC or AV used in
Class,etc. 　

(More Details) PowerPoint.

Learning techniques to be incorporated 　

Suggestions on
Preparation and
Review Be sure to listen and understand lecture contens, because it is an intensive lecture.

Requirements Basic knowledge on control engineering is required.

Grading Method Evaluation is based on the report tasks assigned for each of [1] and [2] above.

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

Other This lecture is given as an intensive course, but some lectures may be held on weekdays for the convenience of the lecturers. You will be notified in advance so that you can make arrangements to attend.

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2024Year	School/Graduate School	Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Smart Innovation Program
Lecture Code	WSS21201	Subject Classification	Specialized Education
Subject Name	データ駆動型スマートシステム特別講義
Subject Name （Katakana）	データクドウガタスマートシステムトクベツコウギ
Subject Name in English	Special Lecture on Data-Driven Smart Systems
Instructor	See the class timetable.
Instructor (Katakana)	ジュギョウジカンワリヲサンショウ
Campus	Higashi-Hiroshima	Semester/Term	1st-Year, First Semester, 2Term
Days, Periods, and Classrooms	(2T) Inte
Lesson Style	Lecture	Lesson Style (More Details)
Lecture
Credits	2.0	Class Hours/Week		Language of Instruction	J : Japanese
Course Level	6 : Graduate Advanced
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	11 : Electrical, Systems, and Control Engineering
Eligible Students
Keywords	Model-based development (MBD), artificial intelligence, neural networks
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)
Class Objectives /Class Outline	This lecture will be divided into two main parts. [1] Model-based development (MBD) in the application of control technology to products. [2] Basic concepts and industrial applications of artificial intelligence.
Class Schedule	[1] (7.5 frames) Although the automotive industry is increasingly trying to develop in line with the MBSE (Model-Based Systems Engineering) approach, the more mature components are lagging behind when it comes to the introduction of control technology. On the other hand, as with other products such as smartphones, upgrading the control technology that forms the backbone is considered essential to improve performance through software upgrades. In this lecture. (1) Problems in the introduction of control technology into vehicle development. (2) 'Functional distribution' utilised to overcome this. (3) Examples of improved control technology. The lecture will cover the following topics. [2] (7.5 frames) Artificial Intelligence (AI) is a discipline that is currently advancing at an ever-increasing pace. Although today's computers have very high processing speeds, they are not as flexible as humans. Artificial Intelligence aims to turn them into "great wits". One of the directions in this direction is to realize computers that can recognise and understand events in the external world, understand natural language and respond to them, just like humans, without the need to create computers and program that can respond flexibly. The aim of this lecture is to introduce the basic concepts of artificial intelligence, pattern understanding systems and problem solving systems for the realization of intelligent robots, with the aim of acquiring basic knowledge of the fundamentals of neurocomputers and the realization of autonomous driving of cars and intelligent robots. Evaluation is mainly based on reports.
Text/Reference Books,etc.	Textbooks will be announced on a bulletin board later.
PC or AV used in Class,etc.
(More Details)	PowerPoint.
Learning techniques to be incorporated
Suggestions on Preparation and Review	Be sure to listen and understand lecture contens, because it is an intensive lecture.
Requirements	Basic knowledge on control engineering is required.
Grading Method	Evaluation is based on the report tasks assigned for each of [1] and [2] above.
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
Other	This lecture is given as an intensive course, but some lectures may be held on weekdays for the convenience of the lecturers. You will be notified in advance so that you can make arrangements to attend.
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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