Lőrincz, András Mészáros, Tamás Pataki, Béla Embedded Intelligent Systems

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15.3.5.1. Ambient intelligence

What is the essence of the Ambient Intelligence (AmI) paradigm? Define the concept of an Intelligent Space! Define the concept of a Smart Home as an information system! What is covered by AAL and AAC abbreviations? What are the special properties of the AmI applications? Characterize the smart home agent taking into consideration its special new problems! What is context? How can you characterize context-aware computing techniques? Elaborate on an example! How can you characterize privacy-aware computing techniques? Elaborate on an example! What is iHCI (Implicit Human Computer Interaction)? Illustrate the answer with an example! List the components of a typical AmI applications?

15.3.5.2. Context

Characterize context-aware system! What are so called AmI scenarios? What is the purpose of the memory prosthesis? What should we expect regarding 'Ambient interfaces for the elderly'? What is the meaning of W5+ (context-aware systems)? List some essential context information in the AmI environment! What processing capabilities are based on the context information? What is context management? When speaking about context information what is a Pull and Push? Characterize the layers of the context processing architecture! What is the context aggregation? Characterize the structured context processing with transformation modules and control processes! What is a context broker and why we need it? What is the purpose of extendble context ontologies? What problems can we encounter in context-aware applications implemented on computationally resource-poor devices? Why it is important to recognize emotions in AmI applications?

15.3.5.3. Architecture

What is hyper reality? What is a channel, a modality, and a multi-modal communication? Compare from the point of view of AmI applications systems with uni(mono)modal and multi-modal HCI! What are the challenges of the AAL applications? What is the principle of 'augmented reality' interfaces? What are the ambient displays?

15.3.5.4. Sensors

What are so called 'serendipitous' sensors? What are the special requirements for picture processing in AmI (AAL) applications? What is the meaning of Activity of Daily Living (ADL)? Why is sensor fusion needed in AmI applications? What are the technical challenges in sensor networks? What is the energy awareness? What is a Kalman-filter model? What is are Sensor Web Enablement Standards (SWE)? What are their components? What are the special properties of the Sensor Web approach? What is SensorML? Characterize the problem of sensor discovery in sensor networks?

15.3.5.5. Control design in AmI

What is the principal problem of the ambient control? What is the principal problem of the (fuzzy) learning in an ambient environment? What is the principle of the Adaptive Online Fuzzy Inference System (AOFIS)? How to identify membership functions form sensory measurement data? How to identify fuzzy rules from sensory measurement data? What is the principle of the online adaptation and 'life-long' learning? What are type-2 fuzzy sets? What is the Foot Print of Uncertainty? What is the primary and secondary membership function in type-2 fuzzy sets? What improvement do we expect from type-2 fuzzy sets? How do we obtain type-2 fuzzy sets? What is the structure of type-2 FLC - Fuzzy Logic Controller? What is the purpose of Karnik-Mendel algoritm? What is the structure of an hierarchical fuzzy system?

15.3.5.6. Planning

What problems must be solved in planning in an AmI applications? Compare the AI planning problem with the general properties of the AmI systems! Why it is important to know, or recognize the user plans? What is the basic principle of the D-HTN? What are the factors influencing the difficulty of the plan recognition problem? What are the problems with the intention recognition in the AmI applications? What is the basic principle of the Probabilistic Horn Abduction? What is the PHATT Probabilistic Hostile Agent Task Tracker? What are the problems when reasoning about the non observable actions from the observed actions? What are the problems when reasoning about the non observable actions from the observed state transitions?

15.3.5.7. Sensor fusion

Characterize the process of building dynamic model of the environment! What basic principles must be taken into account when building a dynamic model of the environment (the world)? What were the assumptions when deriving within the Bayesian scheme the temporal fusion of the single sensor data? Why we cannot call probability the uncertainty describing quantities used by the Dempster-Shafer fusion? What is the difference between the Bayes and Dempster-Shafer fusion? If we have N events, then how do we represent ignorance in the Dempster-Shafer approach? What problems are caused by in the Dempster-Shafer fusion approach by a conflict? How this problem is solved under Bayesian assumptions? How was Dempster-Shafer approach modified by Yager to handle the conflict problem better? What unified conflict handling approach was proposed by Inagaki? Characterize the statically and dynamically weighted Dempster-Shafer approach! Compare the learned sensor fusion approaches! Show that using Yager's rule the combination of 3 events will not be commutative. Show that the modified MOPs of the weighted fusion method sum up to 1 independently from its w weight, if the sum of the original MOPs of the sensor was 1. Show that using Inakagi's unified combination rule with different k parameters the combination of 3 events will be commutative only in the Dempster-Shafer case.

15.3.5.8. Activity

The action series < a b c d a b c d a b c d a b c d a b c d a b c d .... a b c d > having equidistant timing is analyzed. The series consist of 2013 periods of < a b c d>. Give the compression ratio, if the encoding of the time stamps is twice as long as the encoding of the actions.

The granularity used in a daily activity characterization is minute resolution. Give the compression ratio of a two months period using a 27 minute-long episode candidate, which occur every Tuesday and Wednesday exactly starting at 8:13 a.m.

Give the compression ratio of the exercise above if the start time of the episodes in Tuesday and Wednesday is not so strict, it has uniform distribution between 8:00 and 8:30 a.m.

Give the maximal episodes of the action series < a b c d x x c d a b c x x x x x x b c d a b c d .... a b c d > having equidistant timing, if both window capacity and window time are 5. (x is not a real action, it is not important in itself, but < a x b> or < a a x c> could be important.)

Give the important episode candidates using the maximal episodes found in the Exercise above.

15.3.5.9. HCI

How can one influence the brain directly? How can neural prosthetics influence emotions? Explain the differences and the similarities between retinal implants and an active tactile devices! Consider robotic surgery from the point of view of brain-computer interfaces! What is the origin of illusions?

15.3.5.10. Modelling user behaviour

Characterize user modeling in AmI systems! (from the adaptive and personalized point of view) What are personas? How to compute user profiles from personas? What kind of phenomena can be used for emotion estimation? What are the action units of the face? What kind of algorithms are used facial expression estimation? How is the constrained local model built? What is the key assumption? Sketch the key components of an architecture that can model a user! What is an ARX model? How can it be used for control? What is a decision making heuristics? What is the value of an event?