Sensors and sensor networks (3cr)

Objective

The study concentrates on selected up to date technologies on sensors and sensor networks. Configuration and programming assignments will give a deeper understanding.

Content

There will be a number of lessons and laboratory assignments in SeAMK premises in Seinäjoki. In addition to this there will be assignments which can be completed with distance learning methods. For distance learning a computer with network capabilities will be necessary. Most assignments will be done on development environments which can be opened in an Internet browser. On some of these development environments a license granted for people with student status will be necessary. Enrolment as degree student or open university student must be done before the course beginning.
Modern technologies on sensors and sensor networks has been selected for the study. Laboratory assignments will give a practical oriented view on the subject.

Content:
Sensors and proximity switches in industry. Interfacing to PLC. Sensor workshop: analog and digital sensors, signals.
Field bus technologioes, sensor data on the fieldbus. WHART and other wireless networks in industry.

Workshop on IoT sensor, IoT device and IBM Watson IoT platform configurations: Programming a mqtt message generation on a micro controller. Defining IoT devices on IBM Watson IoT platform. Programming the authentication of devices and messages. Programming the sensor value reading into a program generating JSON formatted messages. Presentation of sensor values on IBM Watson IoT Dashboard.

Assignment: Group work assignment as distance learning.

Processing sensor data with IBM Watson Iot using NodeRed.

Applications for Radio Frequency Identification; a demonstration.

Assessment criteria, satisfactory (1)

Minimum 60% of assignments completed. Solutions are based on technologies learned on tutored exercises.

Assessment criteria, good (3)

Minimum 80% of assignments completed. Solutions are based on technologies studied on the course.

Assessment criteria, excellent (5)

Minimum 80% of assignments completed. Creative solutions have been developed applying the technologies studied on the course.