Internet of ThingsLaajuus (6 cr)
Code: ET22EC06
Credits
6 op
Objective
Knowledge and understanding
After completing the course, the student should be able to:
- explain the advantages of using IoT solutions
- define the need for IoT solutions in applications
Skills and Abilities
After completing the course, the student should be able to:
- create simple Node-Red applications
- communicate using Wireless communication
- optimize the availability of data using Cloud services
- analyze the needs for Smart home solutions
Evaluation Ability and Approach
After completing the course, the student should be able to:
- select relevant technology based on application
- justify the choice of technology in IoT applications
Content
Introduction and Raspberry PI
What is IoT and the future
Getting to know Raspberry PI: Installation, Node-red, Dashboard, MQTT
One hands on exercise (Node-Red and MQTT)
Wireless technology
Overview of the wireless technology used today: Bluetooth, Wifi, LoraWAN (and Sigfox), NB IoT with 4G and 5G cellular network
How to connect LoraWAN sensors. LoraWAN commercial network from Digita (national network) and global open network from The Things Network.
Make your own IoT sensor with ESP32 and DS18B20, a battery powered temperature sensor with Wifi.
3 Hands on exercises (Bluetooth & Wifi, LoraWAN and ESP32)
Cloud services for IoT
Basic overview
Azure and/or AWS
One hands on exercise
Smart home
Using cloud services and Raspberry Pi to control and measuring your home.
Using voice control with smart speakers from Amazon and Google.
One hands on exercise
Qualifications
No prerequisites
Assessment criteria, approved/failed
Approved: Active participation in lectures and excercises, approved portfolio
Otherwise, not approved.
Materials
Lecturer's slides and handouts
Reference book:
Exploring Raspberry Pi: Interfacing to the Real World with Embedded Linux by Derek Molloy
Enrollment
01.12.2024 - 09.02.2025
Timing
10.02.2025 - 27.04.2025
Number of ECTS credits allocated
6 op
Mode of delivery
Contact teaching
Campus
Vasa, Wolffskavägen 33
Teaching languages
- English
Degree programmes
- Degree Programme in Energy Technology
- Degree Programme in Electrical Engineering and Automation
Teachers
- Hans Lindén
Teacher in charge
Ronnie Sundsten
Scheduling groups
- ET24 (Size: 40. Open UAS: 0.)
- ELA23-E (Size: 40. Open UAS: 0.)
Groups
-
ET24D-VEnergy Technology, 2024
-
ELA23D-VIngenjör (YH), el- och automationsteknik, 2023, dagstudier
Small groups
- ET24
- ELA23-E
Objective
Knowledge and understanding
After completing the course, the student should be able to:
- explain the advantages of using IoT solutions
- define the need for IoT solutions in applications
Skills and Abilities
After completing the course, the student should be able to:
- create simple Node-Red applications
- communicate using Wireless communication
- optimize the availability of data using Cloud services
- analyze the needs for Smart home solutions
Evaluation Ability and Approach
After completing the course, the student should be able to:
- select relevant technology based on application
- justify the choice of technology in IoT applications
Content
Introduction and Raspberry PI
What is IoT and the future
Getting to know Raspberry PI: Installation, Node-red, Dashboard, MQTT
One hands on exercise (Node-Red and MQTT)
Wireless technology
Overview of the wireless technology used today: Bluetooth, Wifi, LoraWAN (and Sigfox), NB IoT with 4G and 5G cellular network
How to connect LoraWAN sensors. LoraWAN commercial network from Digita (national network) and global open network from The Things Network.
Make your own IoT sensor with ESP32 and DS18B20, a battery powered temperature sensor with Wifi.
3 Hands on exercises (Bluetooth & Wifi, LoraWAN and ESP32)
Cloud services for IoT
Basic overview
Azure and/or AWS
One hands on exercise
Smart home
Using cloud services and Raspberry Pi to control and measuring your home.
Using voice control with smart speakers from Amazon and Google.
One hands on exercise
Materials
Lecturer's slides and handouts
Reference book:
Exploring Raspberry Pi: Interfacing to the Real World with Embedded Linux by Derek Molloy
Evaluation scale
H-5
Assessment criteria, approved/failed
Approved: Active participation in lectures and excercises, approved portfolio
Otherwise, not approved.
Qualifications
No prerequisites
Enrollment
30.11.2023 - 25.02.2024
Timing
12.02.2024 - 28.04.2024
Number of ECTS credits allocated
6 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology and Seafaring
Campus
Vasa, Wolffskavägen 33
Teaching languages
- English
Degree programmes
- Degree Programme in Energy Technology
- Degree Programme in Electrical Engineering and Automation
Teachers
- Hans Lindén
Teacher in charge
Ronnie Sundsten
Scheduling groups
- ELA22-E (Size: 40. Open UAS: 0.)
- ET23 (Size: 40. Open UAS: 0.)
Groups
-
ET23D-VEnergy Technology, 2023
-
ELA22D-VIngenjör (YH), el- och automationsteknik, 2022, dagstudier
Small groups
- ELA22-E
- ET23
Objective
Knowledge and understanding
After completing the course, the student should be able to:
- explain the advantages of using IoT solutions
- define the need for IoT solutions in applications
Skills and Abilities
After completing the course, the student should be able to:
- create simple Node-Red applications
- communicate using Wireless communication
- optimize the availability of data using Cloud services
- analyze the needs for Smart home solutions
Evaluation Ability and Approach
After completing the course, the student should be able to:
- select relevant technology based on application
- justify the choice of technology in IoT applications
Content
Introduction and Raspberry PI
What is IoT and the future
Getting to know Raspberry PI: Installation, Node-red, Dashboard, MQTT
One hands on exercise (Node-Red and MQTT)
Wireless technology
Overview of the wireless technology used today: Bluetooth, Wifi, LoraWAN (and Sigfox), NB IoT with 4G and 5G cellular network
How to connect LoraWAN sensors. LoraWAN commercial network from Digita (national network) and global open network from The Things Network.
Make your own IoT sensor with ESP32 and DS18B20, a battery powered temperature sensor with Wifi.
3 Hands on exercises (Bluetooth & Wifi, LoraWAN and ESP32)
Cloud services for IoT
Basic overview
Azure and/or AWS
One hands on exercise
Smart home
Using cloud services and Raspberry Pi to control and measuring your home.
Using voice control with smart speakers from Amazon and Google.
One hands on exercise
Location and time
According to the schedule
Materials
Lecture slides
Teaching methods
Shorter theory briefings accompanied by hands on tasks that are partly solved during the scheduled time slots and partly at home. Tasks are done in groups of two persons.
Evaluation scale
H-5
Assessment criteria, approved/failed
Approved: Active participation in lectures and excercises, approved portfolio
Otherwise, not approved.
Assessment methods and criteria
All task solutions and documentation of the tasks are gathered into a portfolio. The portfolio is graded. There is no exam.
Assessment criteria, fail (0)
Less than 50% of the tasks have been solved and documented.
Assessment criteria, satisfactory (1-2)
In Between 50% and 69% of the tasks have been solved and documented.
Assessment criteria, good (3-4)
In Between 70% and 89% of the tasks have been solved and documented.
Assessment criteria, excellent (5)
90% or more of the tasks have been solved and documented.
Qualifications
No prerequisites
Enrollment
01.12.2022 - 21.02.2023
Timing
13.02.2023 - 30.04.2023
Number of ECTS credits allocated
6 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology and Seafaring
Campus
Vasa, Wolffskavägen 33
Teaching languages
- English
Seats
0 - 20
Degree programmes
- Degree Programme in Energy Technology
- Degree Programme in Electrical Engineering and Automation
Teachers
- Hans Lindén
Teacher in charge
Roger Mäntylä
Scheduling groups
- ET22 (Size: 30. Open UAS: 0.)
- ELA20-E (Size: 30. Open UAS: 0.)
- ELA21-E (Size: 30. Open UAS: 0.)
Groups
-
ET22D-VEnergy Technology, 2022
-
ELA21D-VIngenjör (YH), el- och automationsteknik, 2021, dagstudier
-
ELA20D-VIngenjör (YH), el- och automationsteknik, h20, dagstudier
Small groups
- ET22
- ELA20-E
- ELA21-E
Objective
Knowledge and understanding
After completing the course, the student should be able to:
- explain the advantages of using IoT solutions
- define the need for IoT solutions in applications
Skills and Abilities
After completing the course, the student should be able to:
- create simple Node-Red applications
- communicate using Wireless communication
- optimize the availability of data using Cloud services
- analyze the needs for Smart home solutions
Evaluation Ability and Approach
After completing the course, the student should be able to:
- select relevant technology based on application
- justify the choice of technology in IoT applications
Content
Introduction and Raspberry PI
What is IoT and the future
Getting to know Raspberry PI: Installation, Node-red, Dashboard, MQTT
One hands on exercise (Node-Red and MQTT)
Wireless technology
Overview of the wireless technology used today: Bluetooth, Wifi, LoraWAN (and Sigfox), NB IoT with 4G and 5G cellular network
How to connect LoraWAN sensors. LoraWAN commercial network from Digita (national network) and global open network from The Things Network.
Make your own IoT sensor with ESP32 and DS18B20, a battery powered temperature sensor with Wifi.
3 Hands on exercises (Bluetooth & Wifi, LoraWAN and ESP32)
Cloud services for IoT
Basic overview
Azure and/or AWS
One hands on exercise
Smart home
Using cloud services and Raspberry Pi to control and measuring your home.
Using voice control with smart speakers from Amazon and Google.
One hands on exercise
Location and time
According to the schedule
Materials
Lecture slides
Teaching methods
Shorter theory briefings accompanied by hands on tasks that are partly solved during the scheduled time slots and partly at home. Tasks are done in groups of two persons.
Evaluation scale
H-5
Assessment criteria, approved/failed
Approved: Active participation in lectures and excercises, approved portfolio
Otherwise, not approved.
Assessment methods and criteria
All task solutions and documentation of the tasks are gathered into a portfolio. The portfolio is graded. There is no exam.
Assessment criteria, fail (0)
Less than 50% of the tasks have been solved and documented.
Assessment criteria, satisfactory (1-2)
In Between 50% and 69% of the tasks have been solved and documented.
Assessment criteria, good (3-4)
In Between 70% and 89% of the tasks have been solved and documented.
Assessment criteria, excellent (5)
90% or more of the tasks have been solved and documented.
Qualifications
No prerequisites