1
课程详述
COURSE SPECIFICATION
以下课程信息可能根据实际授课需要或在课程检讨之后产生变动。如对课程有任何疑问，请
联系授课教师。
The course information as follows may be subject to change, either during the session because of unforeseen
circumstances, or following review of the course at the end of the session. Queries about the course should be
directed to the course instructor.
1.
课程名称 Course Title
光电智感
Optoelectronics Intellisense
2.
授课院系
Originating Department
电子与电气工程系
3.
课程编号
Course Code
EE108
4.
课程学分 Credit Value
3 学分
5.
课程类别
Course Type
专业选修课 Major Elective Courses
6.
授课学期
Semester
春季 Spring
7.
授课语言
Teaching Language
英文 English
8.
授课教师、所属学系、联系方
式（如属团队授课，请列明其
他授课教师）
Instructor(s), Affiliation&
Contact
（For team teaching, please list
all instructors）
沈平、讲席教授、电子与电气工程系、shenp@sustech.edu.cn
Shum Ping, Chair Professor, Department of Electrical and Electronic Engineering 、
shenp@sustech.edu.cn
9.
实验员/助教、所属学系、联系
方式
Tutor/TA(s), Contact
待公布 To be announced
10.
选课人数限额(可不填)
Maximum Enrolment
（Optional）
2
11.
授课方式
Delivery Method
讲授
Lectures
习题/辅导/讨论
Tutorials
实验/实习
Lab/Practical
其它(请具体注明)
Other（Pleasespecify）
总学时
Total
学时数
Credit Hours
48
0
0
0
48
12.
先修课程、其它学习要求
Pre-requisites or Other
Academic Requirements
无 NA
13.
后续课程、其它学习规划
Courses for which this course
is a pre-requisite
无 NA
14.
其它要求修读本课程的学系
Cross-listing Dept.
无 NA
教学大纲及教学日历 SYLLABUS
15.
教学目标 Course Objectives
《光电智感》课程使学生了解人工智能时代下智能感知的基本理论以及常用的传感器测量原理，了解设计传感器时要注
意的基本问题，了解光电传感器的关键技术，了解各种光电传感技术前沿应用及发展。培养学生应用传感器的基本技能和
逻辑思维能力，增强学生的科学素养，使学生具有理论联系实际能力，为国家未来信息领域发展培养高层次复合型人才。
The course aims to enable students in the era of artificial intelligence to understand the basic theory of intellisense
and common sensor measurement principles, understand the basic issues when designing sensors, understand the key
technologies of photoelectric sensors, and understand the frontiers of various optoelectronics sensing technologies as
well as its application and development. The course aims to cultivate students' analytical skills in applying sensors,
enhance students' scientific literacy, enable students to have the ability to integrate theory with practice, and cultivate
high-level compound talents for the development of modern information field.
16.
预达学习成果 Learning Outcomes
1：学生了解传感的基本理论以及常用的传感器测量原理；掌握数学、自然科学知识，能够将数学、自然科学、工程基础
和专业知识运用于信息工程的复杂工程问题的恰当表述。
2：学生基于传感基础知识具有理论联系实际能力，能够应用数学与自然科学基本原理、工程基础与专业知识，对复杂
信息系统和过程进行识别和准确表达，
3：学生了解设计传感器及传感系统要注意的基本问题及需求，能够掌握本专业涉及的工程设计概念、原则和方法，能
够针对信息领域的复杂工程问题确定设计需求。
4：培养学生在传感领域方面的书面报告、口头沟通的专业技能和科学素养，对信息领域复杂工程问题，能够以书面和
口头形式表达设计思想、方法及成果，与业界同行及社会公众进行有效沟通和交流。
1: Students understand the basic theory of sensing and commonly used sensor measurement principles; master
mathematics and natural science knowledge, and be able to apply mathematics, science, engineering foundation and
professional knowledge to the appropriate expression of complex engineering problems in information engineering.
2: Students can integrate theory with practice based on basic sensing knowledge, and can apply basic principles of
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mathematics and science, engineering foundations and professional knowledge to identify and accurately express
complex information systems and processes.
3: Students can understand the basic issues and requirements that should be paid attention to when designing
sensors and sensing systems, can master the engineering design concepts, principles and methods involved in the
major, and can equip with analytical skills that determine design requirements for complex engineering problems in the
information field.
4: Cultivate students' written reports, oral communication professional skills and scientific literacy in the field of
sensing, and be able to express design ideas, methods and results in written and oral presentation, and conduct with
industry peers and the effective public communication.
17.
课程内容及教学日历 （如授课语言以英文为主，则课程内容介绍可以用英文；如团队教学或模块教学，教学日历须注明
主讲人）
Course Contents (in Parts/Chapters/Sections/Weeks. Please notify name of instructor for course section(s), if
this is a team teaching or module course.)
Chapter 1 Industrial Applications of Artificial Intelligence 3 Teaching Hours
1.1 Introduction of AI
1.2 Key technologies of AI
1.3 Industrial applications of machine learning
第一章 人工智能及其工业应用 3
学时
1. 1 人工智能概述
1. 2 人工智能关键技术
1.3 机器学习及其工业应用
Chapter 2 IoT and Intellisense 3 Teaching Hours
2.1 Introduction of IoT
2.2 Key technologies of IoT
2.3 IoT and sensing technologies
2.4 IoT based optoelectronics intellisense
第二章 智能物联与感知技术 3
学时
2. 1 概述
2. 2 物联网的关键技术
2.3 物联网与传感技术
2. 4 基于物联网的光电传感技术