TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF ENGINEERING |
| ELECTRICAL-ELECTRONIC ENGINEERING PR. (ENGLISH) | |
| Code | EEES415 |
| Name | Introduction to Internet of Things (IoT) |
| Term | 2019-2020 Academic Year |
| Semester | 7. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Belirsiz |
| Type | Normal |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi ERCAN AVŞAR |
| Course Instructor |
Dr. Öğr. Üyesi ERCAN AVŞAR
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
Introducing the IoT concept, gaining theoretical and practical knowledge required for development of IoT applications
Course Content
IoT concepts, Technological background of IoT, Introduction of required platforms for IoT application development, Introduction to Python programming language, Object types in Python: numbers, strings, lists, Conditions, loops and functions in Python, Single board computers, microcontrollers and sensors for IoT applications, Single board computer programming programming with Python, reading data from sensors and controlling actuators, Serial communication protocols: SPI and I2C, Internet communication and principal protocols: HTTP, IP, TCP, UDP, Connecting the single board computer to internet: WiFi and Ethernet connections, Basic HTTP methods: GET, POST, PUT, Methods on local database: reading and writing of sensor data, Methods on cloud database: reading and writing of sensor data, Processing of sensor data and constructing a simple decision model
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Comprehends the concept of IoT and its importance |
| LO02 | Gains coding ability for IoT applications |
| LO03 | Recognizes and uses the hardware developed for IoT applications |
| LO04 | Collects data from sensors and processes them |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems. | 4 |
| PLO02 | - | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | 5 |
| PLO03 | - | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | 5 |
| PLO04 | - | Ability to devise, select, and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ computer programming techniques, and information technologies effectively. | 5 |
| PLO05 | - | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | 4 |
| PLO06 | - | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | 5 |
| PLO07 | - | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, | 5 |
| PLO08 | - | Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | 5 |
| PLO09 | - | Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice. | 5 |
| PLO10 | - | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | 5 |
| PLO11 | - | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | 5 |
| PLO12 | - | Ability to apply the knowledge of electrical-electronics engineering to profession-specific tools and devices. | 5 |
| PLO13 | - | Having consciousness about the scientific, social, historical, economical and political facts of the society, world and age lived in. | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | IoT concepts | None | |
| 2 | Technological background of IoT. Introduction of required platforms for IoT application development. | Review the previous lecture contents | |
| 3 | Introduction to Python programming language. Object types in Python: numbers, strings, lists | Review the previous lecture contents | |
| 4 | Conditions, loops and functions in Python. | Review the previous lecture contents | |
| 5 | Single board computers, microcontrollers and sensors for IoT applications. | Review the previous lecture contents | |
| 6 | Single board computer programming with Python, reading data from sensors and controlling actuators. | Review the previous lecture contents | |
| 7 | Serial communication protocols: SPI and I2C | Review the previous lecture contents | |
| 8 | Mid-Term Exam | Review the previous lecture contents | |
| 9 | Internet communication and principal protocols: HTTP, IP, TCP, UDP | Review the previous lecture contents | |
| 10 | Connecting the single board computer to internet: WiFi and Ethernet connections | Review the previous lecture contents | |
| 11 | Basic HTTP methods: GET, POST, PUT | Review the previous lecture contents | |
| 12 | Methods on local database: reading and writing of sensor data | Review the previous lecture contents | |
| 13 | Methods on cloud database: reading and writing of sensor data | Review the previous lecture contents | |
| 14 | Processing of sensor data and constructing a simple decision model | Review the previous lecture contents | |
| 15 | Review | Review the previous lecture contents | |
| 16 | Term Exams | Review the previous lecture contents | |
| 17 | Term Exams | Review the previous lecture contents |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 70 | 28 |
| 1. Oral Exam | 30 | 12 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |