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Smart Environments and Services (4 cr)

Code: DT10043-3001

General information


Enrollment

01.04.2024 - 30.04.2024

Timing

26.08.2024 - 20.12.2024

Number of ECTS credits allocated

4 op

Mode of delivery

Contact teaching

Campus

Wärtsilä Campus Karjalankatu 3

Teaching languages

  • Finnish

Seats

10 - 70

Degree programmes

  • Degree Programme in Business Information Technology

Teachers

  • Ossi Laakkonen
  • Jarmo Talvivaara

Teacher in charge

Ossi Laakkonen

Groups

  • DTNS22
    Information Technology (BBA), Full-time Studies, Fall, 2022

Objective

You will know the basic principles, implementation methods, advantages and possibilities of smart environments, services and other intelligent solutions, as well as examples of application targets.
You know the importance of data and the different roles behind smart and intelligent solutions
You can collect data that can be used to implement smart environments.
You can evaluate the quality and suitability of the collected data in the implementation of intelligent solutions.
You know the principles of the importance, role and application of different aspects of machine learning in enabling the implementation of intelligent solutions.
You know and know how to apply the most typical technologies in the implementation of intelligent solutions (eg advanced Internet of Things technologies, digital twins, intelligent edge computing, intelligent automation and robotics)
You know the importance of integration solutions and APIs in intelligent solutions.
You can apply integration solutions and APIs that utilize intelligent solutions.
You know, know how to model and evaluate the architectures of smart environments and other intelligent solutions.
You are familiar with different examples and special cases of smart environments and other intelligent solutions.
You get familiar and be able evaluate risks of cyber-security in intelligent solutions and are able to design actions how to improve security.
You will know the possibilities of high-power and quantum computing in improving the solution of computational problems in intelligent solutions.

Content

Intelligent environments, services, equipment, materials.
Autonomous systems: robotics and cybernetics, software, cyber-physical solutions.
Smart platforms
- Roles and utilization of data in intelligent solutions.
- Machine learning applications in intelligence.
- APIs, integrations, architectures
- Design and implementation technologies: intelligent robotics, digital twins, intelligent edge computing (Edge AI)
Case studies and special cases
- digital and virtual environments
- self-driving vehicles
- physical, simulated and virtual robots, cyber-physical solutions.
- smart materials
- wearable technology
- smart spaces and environments
- intelligent processes
- artificial intelligence in cyber-security
Cyber-security in intelligent solutions.
Possibilities of high performance and quantum computing in the applications of intelligent solutions.

Evaluation scale

H-5