Embedded Intelligent Systems

One of the decisive trends nowadays is the appearance of informatics in everyday environments and gadgets. So called ambient environment surrounding the human user reacts to his/her verbal, manual orders, to the gestures, to the face mimics. The environment on its own seeks problems to solve, estimates the emotional state of the humans and on its basis adjusts the environmental parameters. The aim of the subject is a multi level analysis of the information technologies required to realize ambience in the environments, starting from the information infrastructure, up to ambient intelligent spaces encapsulating human users. The subject deals furthermore with the agent based realization of the embedded systems, and with their cooperative behavior. Particular emphasis is put on the intelligence of the sensor networks, on its fusion with the agent based systems. We expect that the students successfully fulfilling the requirements of the subject will have a clear view of the problems of the ambient intelligence and “pervasive computing”, and of the intelligent methods applicable to the embedded systems, will be able to design and analyze intelligent sensor networks, will gain working knowledge of how to analyze problems calling for ambient solutions and how to specify systems to realize ambient intelligent environments.  

Theoretical part of the curriculum is taught during the lectures. Practical experimentation is supported by the home work, software demonstrations during the lectures, and by the related laboratory practice.  

Lecture notes made available at the home page of the subject, suggested electronic literature and additional information, and a web link collection.  ; Wooldridge, M., An Introduction to Multi-agent Systems, J. Wiley, 2002  ; Stuart Russell and Peter Norvig: Artificial intelligence. The modern approach, 2nd edition, Prentice Hall, 2001  ; T. Mitchell: Machine Learning, McGraw-Hill, 1997.  ; F. L. Bellifemine, G. Caire, D. Greenwood: Developing Multi Agent Systems with JADE, Wiley, 2007  ; Sensor Modelling, http://www.opengeospatial.org/standards/sensorml  ; Voting Systems, http://pj.freefaculty.org/Ukraine/PJ3_VotingSystemsEssay.pdf  ; G. Riva, F. Vatalaro, F. Davide, M. Alcañiz (eds.), Ambient Intelligence. The evolution of technology, communication and cognition towards the future of human-computer interaction, http://www.emergingcommunication.com/volume6.html  ; Auction Theory, http://ocw.mit.edu/NR/rdonlyres/Engineering-Systems-Division/ESD-260JFall2003/2CECCCEB-0165-42A3-B86A-B4BBA5A6930B/0/l18ch22auctheory.pdf  

Artificial intelligence. Programming techniques (Java). Cooperative systems. Embedded systems.  

Requirements: a. During the semester:   ·         A home assignment to be handed out in the mid of the semester. Reports with the solutions are due on the 13th week of the semester. The joint presentation of the solutions and the qualification (assuming the reports are ready) is on the 14th week of the semester. The assignment brings max. 20 points, the required minimum is 40%. b. During the supplementary week: advanced oral exam. Students qualify for the final exam with minimal level achievements in home assignment (40 %). c. During the examination period: oral exam. Students qualify for the final exam with minimal level achievements in home assignment (40 %). d. Qualification: The final mark is based on the number of points collected from the home work and the final exam.     Additional possibilities: Failed home assignment can be handed in until the end of the supplementary week.  

Artificial intelligence (BSc), Cooperation and intelligence (MSc). Machine learning (BSc).