Ambient Services framework application in eight sites

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Ambient Services framework application in eight
sites

• Maria Panou, Evangelos Bekiaris, Marion Wiethoff

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ASK-IT sites
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Application scenarios per site

• Relevant Use Cases.
• User groups.
• Time period.
• Existing services to be connected.
• New services to be connected.
• Existing services to be enhanced and connected.
• Short description of application
  scenario/assigned task.
• Content to be used.
• Test location (in-car, home, city centre, ).
• Type of technology to be used.
• Equipment to be used.
• Types of added value services and support tools
  to be supported.
• Success scenarios.
• Failure scenarios.

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Indicative Use Cases per site
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2/2
Indicative Use Cases per site
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Application scenario example - 1
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Application scenario example - 2
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New/existing content connection to ASK-IT
CERTH/ITI DMM tool
Existing, as web content
Connect to ASK-IT
http//askit.iti.gr/
Services to satisfy the UCs
Make it web service, with ASK-IT ontology
Existing as content (no web)
ASK-IT available
http//askit.iti.gr/ontology
Collect data on site
No existing
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Ambient Intelligence in application scenarios - 1

• Within ASK-IT pilots, a vast array of Ambient
  Intelligence services will be tested.
• In the plan a trip, use case the system will
  store the users selections and thus gradually
  learn the user. After a certain number of trips
  planning, the system will know the maximum
  distance the user is willing/able to walk during
  multimodal trips and the maximum number of
  interchanges that will accept to do and thus,
  filter out any unsuitable solution.
• In the find a POI use case, the preferences of
  users on each POI type (i.e. 4 start hotels,
  Mexican and Indian food preferred, vegetarian
  restaurant never selected, etc.) will be taken
  into account in filtering the POIs returned by
  the system.

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Ambient Intelligence in application scenarios - 2

• Services will not only be prioritised and
  filtered according to users disabilities/residual
  abilities, as well as personal preferences, but
  also according to context of use (i.e. allow
  touristic info to be pushed to the user if he/she
  is travelling as tourist but not if his/her
  profile is that of a commuter) and the
  environment (i.e. filtering or adapting several
  services while the user is driving, to safeguard
  road safety).
• User shortcuts will be self-defined, following
  the most frequent patterns of use (i.e. storing
  routes or POIs at users preferred format,
  directory, etc.).

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Combinations and integration

• The above ambient intelligence parameters are not
  considered only as stand alone but also in a
  combined array. For example, in-vehicle info
  provision does not depend only upon whether the
  vehicle is stationary or moving but also upon key
  driver characteristics, such as his/her reaction
  time, average TTC and TLC (all automatically
  estimated).
• Info on the optimal route to reach a POI as
  pedestrian takes into account environmental
  factors, such as the weather at the given day or
  the forecasted weather (if in the future).
• Loyalty schemes (i.e. frequent use of a specific
  rent-a-car company) and obligations (i.e.
  studying through eLearning courses) are dully
  taken into account and follow the user throughout
  his/her trips.

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Conclusion

• ASK-IT is expected to become given also its
  pilots number and actors involved the biggest
  to-day Ambient Intelligence environment
  experiment, a true Living Lab for introducing
  such concepts and technologies to the everyday
  life of all of us.