The goal of this course is to introduce students into the organization, structure and internal vision of the operating systems necessary for Internet of Things systems. Students will learn the services that integrate sensor and actuator based systems and understand the influence that design decisions have on the behavior of an Internet of Things System. In order to archive this goal, the student have to acquire several generic skills, knowledge, capacities and attitudes.
General/transversal competences:
- Analysis and synthesis capacities
- Abilities to organize and to plan
- Problem resolution abilities
- Capacity to apply theoretical concepts
Specific competences:
- Cognitive (knowledge)
1. Know the different types of devices and operating systems of an Internet of Things System.
2. Know different types of use and applications of IoT technology in today's society.
3. Know the structure of an Embedded Operating System that allows the operation of sensors and actuators to be controlled.
4. Know the criteria for selecting the Embedded Operating Systems necessary to control sensors and actuators.
5. Know the programming interfaces (APIs) that embedded systems provide to customize the operation of sensors and actuators.
6. Know the fundamentals for programming IoT devices through the APIs provided by the Embedded Operating Systems.
7. Know operating systems and base platforms to manage clouds of IoT devices.
8. Know the fundamentals of operating systems to package and virtualize microservices to manage clouds of IoT devices.
- Procedimental/Instrumental (Know how)
1. Configure the Hardware and Operating System that controls the operation of sensors and actuators
2. Program the basic operation of IoT devices using the APIs provided by the Operating System.
3. Program basic microservices for IoT device cloud management
4. Virtualize microservices to manage IoT device clouds
- Attitudinal (To be)
1. Critical attitude towards the internal architecture of current IoT systems.
2. Concern for the quality of the components of an IoT system.
3. Motivation for archiving better solutions.
4. Self-learning capacities.