ID2012 Ubiquitous Computing 7.5 credits

Introduction to the field of ubiquitous computing including objectives of the field, core technologies, applications and implications for society. Core technologies are innovative materials, design of new computational artifacts, sensor technology, middleware for fine grained distributed systems, context aware systems, theory of complex systems, artificial intelligence techniques for coordination of behaviour (multi agent systems) and new forms of interaction. A specialization in middleware for ubiquitous computing with a bias on support for collaborative applications, context aware functionalities and tangible interfaces.

On successful completion of this course the student has knowledge and understanding regarding:      

• the objectives and the historical development of the field of ubiquitous computing
• development in new materials
• fundamentals of sensor technology and sensor networks
• design of new (often embedded) interactive artefacts
• contextaware and adaptive systems
• middleware for fine-grained distributed systems
• analysis and coordination of complex systems
• new styles of interaction, e.g. tangible interfaces
• most important applications in the field
• general implications of the field. 

Skills and capacities, to be able to: 

• apply middleware techniques to implement ubiquitous computing systems
• design and implement coordination schemes for systems with many software and hardware components
• design and implement simple context aware applications, using standard sensor technology
• design and implement interfaces suitable for ubiquitous computing in particular tangible interfaces. 

Values and attitudes, to be able to:

• compare the usability of alternative design of interactions for specific ubiquitous computing systems
• compare the adequacy of alternative coordination strategies for specific ubiquitous computing systems
• judge the user acceptance and relevance of specific designs for adaptive and context aware systems
• compare the adequacy of alternative middleware techniques for particular ubiquitous computing systems. 

Basic courses in mathematics, computer science, human computer interaction, artificial intelligence and programming of distributed systems.

If the course is discontinued, students may request to be examined during the following two academic years.

• INLA - Assignment, 1.5 credits, grading scale: P, F
• LABA - Laboratory Work, 3.0 credits, grading scale: A, B, C, D, E, FX, F
• SEM1 - Seminar, 3.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Assessment on the course consists of three assignments. To pass the whole course requires pass on all three.

Fredrik Kilander

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.