Context Aware and Device Dependent Interaction in Smart Environments
Supervisors: Fulvio Corno Dario Bonino Luigi De Russis Candidate: Emanuele Furci
Politecnico di Torino
Master degree in Computer Engineering
Academic year 2013-2014
in Smart Environments Candidate: Supervisors: Emanuele Furci - - PowerPoint PPT Presentation
Politecnico di Torino Master degree in Computer Engineering Context Aware and Device Dependent Interaction in Smart Environments Candidate: Supervisors: Emanuele Furci Fulvio Corno Dario Bonino Luigi De Russis Academic year 2013-2014
Supervisors: Fulvio Corno Dario Bonino Luigi De Russis Candidate: Emanuele Furci
Academic year 2013-2014
Introduction Thesis work
Data Modelling Software Development
Scenario Test Case Conclusions
Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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An intelligent notification system for smart
Take into account the surrounding context to
Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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create a data modelling infrastructure able to
develop a software to elaborate data model
Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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Definition of the Domain of Interest
Users User Devices Smart Home Message Categories
Ontology-Based Modelling Exploration of existing ontology for
Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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4 directly imported ontologies
Locont Device DogOnt Core
27 overall imported ontologies 1385 classes
Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
Activity (e.g. eating, sleeping) Accessibility (e.g. freeable_hands) Location (e.g. livingroom, kitchen) Obtrusiveness (e.g. mobile_only, no_audio) End-User-Devices (e.g. smartphone, tablet) Message Categories (e.g. AppliancesAlert)
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
Physical Features (e.g. screen size, camera) Capabilities (e.g. audio and video
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
Architectural aspects (e.g. wall, window) Appliances (e.g. oven, HVAC system) Devices (e.g. smart tv, HiFi system) Furniture (e.g. couch, table)
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
Priority (e.g. lower_level, highest_level) Attributes (e.g. min_temperature_value)
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Introduction – Data Modelling – Software Development – Experimental Results - Conclusions
Information as Class instance Instance data properties Connections by means of object properties
A single .owl file as data model
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2 users (Luca, Giulia) 3 devices (LG Nexus 4, Samsung Galaxy
1 smart home (temperature and humidity
6 message category (EnvironmentalComfort,
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Data Model Management
Notont Manager
User Interfacing
UserManager
House Interfacing and Message Generation
House Message Manager
Device Message Delivery
Device Manager
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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process
(Obtrusiveness level, Location, etc)
are known
Messages
Notont Manager
Messages
Notont Manager
Android – Based
Gcm Service Mobile application
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2 users (Luca, Giulia) 3 devices (LG Nexus 4, Samsung Galaxy
1 smart home (temperature and humidity
6 message category (EnvironmentalComfort,
Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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Introduction – Data Modelling – Software Development – Scenario Test Case - Conclusions
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Notont – Notification Ontology
Formal representation of context information in
Smart Environments
Inferring of the most suitable end user device
NINS – Notont-based Intelligent Notification
Data model Management House and User interfecing Sending messages to devices
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Test in a real home setting Usage of the context to infer “how” send a
Increase supported devices
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