Advanced sensor systems ET8008 Fall 2009 hh.se/et8008

1. Advanced sensor systems ET8008Fall 2009http://www.hh.se/et8008

2. Course examiner: Stefan Byttner (Stefan.Byttner@hh.se) Room E505 Lecture schedule: Thursday 3 sep: Introductory lecture (Stefan Byttner) Tuesday 8 sep: Camera and vision (Josef Bigun) Thursday 10 sep: State of the art in physics, nano sensors (Håkan Petterson) Thursday 17 sep: Virtual sensors for control (Ulf Holmberg) Tuesday 22 sep: Virtual sensors for monitoring (Antanas Verikas) http://www.hh.se/schema press “Schema för flera veckor”. Select “In english” on the top right. Then you can search for the course and see the schedule details.

3. Project work Deeper study of a particular field of sensors/application. Give some experience in writing a research report. Possible project examples; • Review of state of the art of certain sensors • Experimental evaluation of a sensor setup • Applications to industrial problems Course examination: • Presentation of a related research paper • Writing of a research report of the project (6 pages or more depending on format) and oral presentation of the results at a seminar

4. Project work (cont.) Each project will be done by student groups of 2 students each. Any deviations from this groupsize will be exceptions and must be approved by examiner. They must be approved before project work starts. Seminar with oral presentation of the project work + presentation of the related paper: 22 Oct 13.15-17 Room D415 Written report sent to course examiner email adress as a PDF file no later than: 1 Nov 23:59 (Stefan.Byttner@hh.se)

5. Project work (cont.) • The report/paper should have a similar type of structure as the example papers that are handed out from previous year • It is very important that the report contain some references/review of earlier (related) work to your chosen project topic • In addition to your own work, you need to present a paper at the seminar. Choose the subject of the paper so that it is related to your own work (paper choice should be approved by the examiner once projects have been chosen).

6. Project work (cont.) • Fill out the paper which will circulate the class room after the lecture and decide who will be in each group by yourselves. • I will email each group with project abstracts, each group then needs to send me their rank on each project (rank 1 – most interesting project, rank 2 – second most interesting project, etc). I will use this for deciding which group gets to do a certain project. It is possible that there will be more than 1 group working on the same project.

7. Grading criterions • Adopted partly from master thesis grading • May not need all criterions to be fulfilled to achieve a certain grade

8. Grading criterions (cont.) Information Retrieval Grade 3 Has compiled a satisfactory list of references. Knows which references are important and which are less important for the project. Can summarize the most important references. Knows the contents of the remaining references in “abstract” form. Understands the problem and can formulate subproblems. Can relate the project to the references. Grade 4 Can relate the references to each other and combine information from them and come to conclusions. Can use the references to sharpen the project plan, i.e. decide to omit some studies or concentrate on some subproblem. Grade 5 Is able to criticize and find weak and strong parts in reference articles as well as the own work.

9. Grading criterions (cont.) Results Grade 3 The result is acceptable, but can point at several things that, with a reasonable effort, would have improved it. Can identify and formulate significant strong and weak points in the result. Grade 4 The result is good (i.e. matches well to the anticipated results in the, possibly revised, project plan) and can point at only a few things that could have been done better or that are missing. Can, with minor supervision, come to some conclusions on how the result could have been improved. Can, with minor supervision, formulate some future directions for the project. Grade 5 The result is excellent and the supervisor can point at only very few minor improvements which could have been done. The result is publishable in a scientific journal or at a conference. Can, without supervision, evaluate the result in relation to other work done in the field.

10. Grading criterions (cont.) Presentation Grade 3 Presents the problem and proposed solution in a clear way. Presents a clear analysis of the problem. Can answer fundamental questions on the subject. Grade 4 Presents the project in an attractive way with e.g. well chosen illustrations. Can discuss different aspects of the problem. Grade 5 An excellent presentation, which engages the audience and generates interested questions. All questions are answered in a relevant way.

11. Grading criterions (cont.) Report Grade 3 The report is complete (i.e. with ”background”, ”methodology”, ”results”, ”conclusion”, ”summary” etc.). All references, figures & tables are referred to in the text. Grade 4 The report is, with significant supervision, well written. (”Well written” means that: The English is correct and the text flows smoothly. Figures are relevant and add value to the text. Similarly with tables. The result and conclusion is clearly stated.) Grade 5 The report is, with minor supervision, very well written. The report is written such that it would be publishable, provided the result is good enough.

12. Overview of the sensorbased research at EIS

13. Research: Physics of Nanoscale Devices Electrical, optical and magnetic properties of nanoscale devices Performed in co-operation with the Nanometer Structure Consortium at Lund University 1nm

14. Research: Signal analysis • Biometric identification by combining different modalities (lip movements, face, fingerprints,...) • Biometric communication. Speech data Visual data Fusion system Recogniser Verification results Reject/Accept

15. Research: Paper industry Real time quality measurements (soft sensors) for paper making Machine learning, optics, spectroscopy Shrinking, deinking, …

16. Research: Print quality Machine learning and image analysis to measure color reproduction in printed media. Now for real-time feedback control Used by (e.g.) Hallandsposten and Bank of England.

17. Research: Control theory Neural network Ion current Air/fuel ratio Pressure Burn rate Robust estimation Robust control • Real-time on-road system • DELPHI/GM transfer 99-00 • The best algorithm for this that DELPHI has tried. • Product in DELPHI today Under the hood of our highway laboratory, a SAAB 9000 2.3 T

18. Research: Vehicle monitoring Information communicated using wireless technology Vehicle DataVehicle Health • Causes for Anomalies : • Physical Faults • Operational Abnormalities • Deterioration Compare and Identify Fleet behavior can provide a norm in which an “unhealthy” bus can be detected as deviating from the norm. The RDM project investigates how this norm can be found and used on a fleet of vehicles to improve up-time management. FleetHealth Status

19. Research: Robotics Autonomous robots for agriculture (weeding, sowing, etc.)

20. Research: Robotics MultipleAutonomous Forklifts for Loading and Transportation Applications

21. Research: Intelligent home • An intelligent environment with sensors. • For assisting elderly people living there. • Detecting risks of falling, deviations from daily pattern of activities, etc...