Cognitive Cyber-physical Systems: from theory to practice

The integrated course will be delivered by Prof. C.Alippi and Prof. M. Roveri

MISSION AND GOALS

This course has been thought for Ph.D. and Master students willingly to learn and understand the technical and technological solutions as well as the theoretical and methodological aspects in the design and development of the future generation of cognitive cyber-physical systems.

SUBJECT AND PROGRAMME OF THE COURSE

The course presents the theoretical and practical aspects in designing cyber-physical systems featuring intelligent skills. More specifically, the course addresses the following aspects:
– From smart objects to intelligent cyber-physical systems
– Wireless/wired/hybrid technological solutions and architectures for cyber-physical systems
– Smart Sensing for smart systems
– Designing embedded hardware, software and algorithms: robustness analysis and Probably Approximately Correct Computation
– Smart Energy Harvesting and Management
– Cognitive mechanisms for cyber-physical systems

INSTRUCTION LANGUAGE

English

IMPORTANT: Lesson #2 (04/02/2016) has been cancelled due to health reasons of the lecturer. Further details will follow.

 

SCHEDULE OF THE COURSE (tentative)

Lesson Schedule Room Time
1 28/01/16 Seminari (DEIB) 13.30-17.30
CANCELLED 04/02/16 Seminari (DEIB) 13.30-17.30
3 11/02/16 Seminari (DEIB) 13.30-17.30
4 18/02/16 Seminari (DEIB) 13.30-17.30
5 25/02/16 Seminari (DEIB) 13.30-17.30
2bis 01/03/16 Conferenze (DEIB) 13.30-17.30
6 03/03/16 Conferenze (DEIB) 13.30-16.00

TEACHING ORGANIZATION

The aspects presented in the course are both technological and methodological and real-world applications of Cognitive Cyber-physical Systems will be presented and discussed.

TEACHING MATERIALS

  • Slides and Codes provided by the lecturers
    • Lecture 1 (Intro)
    • Lecture 2 (From measurements to smart sensors)
    • Lecture 3 (Cognitive (model-free) learning and adaptation mechanisms – Part 1)
    • Lecture 4 (Problem Complexity and Complexity Reduction by Prof. C. Alippi)
    • Lecture 5 (Cognitive (model-free) learning and adaptation mechanisms – Part 2)
    • Lecture 6 (Emotional cognitive mechanisms for cyber-physical systems)
    • Lecture 7 (Adaptation mechanisms in embedded systems)
    • Matlab Exercises (Practical Lecture)
    • Course Projects
  • Reference book: “Intelligence for Embedded Systems: A Methodological Approach”, C. Alippi, Springer, 2014

LEARNING EVALUATION

Project/Thesis