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Context Reasoning and Prediction
in Smart Environments:
the Home Manager case
IIMSS 2017
Algarve - Portugal, 23 June 2017
...
Outline
• Scope & Goals
• Smart Environments in the Butlers perspective
o The Butlers Vision
o The Home Manager Platform
o...
Scope & Goals (1/2)
Smart Environments socio-technical nature calls for
from diverse fields  multi-paradigm perspective
R...
Framework for the design & development
of Smart Environments
• accounting for technological and human / organisational asp...
The Butlers Vision
• Butlers for Smart Spaces specialises the Butlers framework
to the Smart Spaces context
• Home Manager...
Butlers for Smart Spaces…
Specialisation of the Butlers framework to the Smart
Spaces context
The Monitoring layer groups ...
…on Home Manager as a MAS
Home Manager (apice.unibo.it/xwiki/bin/view/Products/HomeManager)
concretises it as a MAS on the...
The Home Manager platform
• Open source platform for Smart Spaces, built on top of the
TuCSoN multi-agent infrastructure
o...
Intuitive architecture
Main features:
o Autonomous “situated” decisions by exploiting the user’s location
o Exploration of...
Smart Environments in HM
• Designing a Smart Environment in Home Manager amounts to:
o identify relevant device and servic...
The Smart Kitchen Case Study
• Smart Fridge & Smart Pantry
o food monitoring
o collecting historical data on user’s habits
o generate the corresponding...
The Smart Kitchen: prototype
Middleware  coordination laws  interoperability & integration
• Declarative approach
o brid...
Future (current) work
Context prediction & adaptation: prediction agent
WEKA Classifier (Ilaria Bertoletti Master's thesis...
Future (current) work
Context prediction & adaptation: prediction agent
WEKA Classifier (Ilaria Bertoletti Master's thesis...
Future (current) work
Context prediction & adaptation: prediction agent
WEKA Classifier (Ilaria Bertoletti Master's thesis...
Future (current) work
Context prediction & adaptation: prediction agent
WEKA Classifier (Ilaria Bertoletti Master's thesis...
Home Manager lays the foundations to support
context reasoning and context prediction
• Yet, just a starting point..
• A l...
Conclusions (2)
Future work
• Deeper exploration of the context reasoning aspect
(machine learning,…)
• Cross-platform int...
Home Manager URLs
• Home page
http://apice.unibo.it/xwiki/bin/view/Products/HomeManager
• Bitbucket repository
https://bit...
Roberta Calegari roberta.calegari@unibo.it
Enrico Denti enrico.denti@unibo.it
http://www.unibo.it
http://www.cse.unibo.it/...
Prototype screenshots
Smart kitchen
simulated device vs physical device
Mixer agent
Prototype screenshots
Smart kitchen
cooking requests
missing ingredients
Prototype screenshots
Smart oven
demo implementation
Prototype screenshots
Smart fridge
demo implementation
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Context Reasoning and Prediction in Smart Environments: the Home Manager case

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Presentation given at IIMSS conference, Vilamoura, June 2017

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Context Reasoning and Prediction in Smart Environments: the Home Manager case

  1. 1. Context Reasoning and Prediction in Smart Environments: the Home Manager case IIMSS 2017 Algarve - Portugal, 23 June 2017 Roberta Calegari, Enrico Denti
  2. 2. Outline • Scope & Goals • Smart Environments in the Butlers perspective o The Butlers Vision o The Home Manager Platform o The Home Manager Architecture • Smart Environment in HM • The Smart Kitchen Case Study o The Smart Kitchen: Scenario o The Smart Kitchen: Prototype • Conclusions & Future Work
  3. 3. Scope & Goals (1/2) Smart Environments socio-technical nature calls for from diverse fields  multi-paradigm perspective REQUIREMENTS • availability of an effective coordination middleware • effective support to situatedness • guidelines and enabling techniques exploiting concepts, methodologies, technologies from the most diverse fields, in a multi-paradigm perspective • skills • concepts • methodologies • technologies
  4. 4. Framework for the design & development of Smart Environments • accounting for technological and human / organisational aspects • combining different dimensions and behaviour from pervasive, distributed, situated and intelligent computing Scope & Goals (2/2) Butlers for Smart Spaces • technology-neutral • reference framework • focused on users’ situated- ness and interaction aspects Home Manager • platform for Smart Home & Smart Living contexts • focused on reasoning aspects • multi-paradigm, agent-based
  5. 5. The Butlers Vision • Butlers for Smart Spaces specialises the Butlers framework to the Smart Spaces context • Home Manager leads to concretise it as a multi-agent system on the TuCSoN infrastructure
  6. 6. Butlers for Smart Spaces… Specialisation of the Butlers framework to the Smart Spaces context The Monitoring layer groups together the Butlers information and control layers The Services layer embeds the coordination referring to the pre-processing of raw information into exploitable knowledge Goals & Policies side-by- side take into account user- awareness (user-related, higher-level coordination) The Reasoning & Situated Reasoning layers split the Butlers Intelligence layer
  7. 7. …on Home Manager as a MAS Home Manager (apice.unibo.it/xwiki/bin/view/Products/HomeManager) concretises it as a MAS on the TuCSoN infrastructure The TuCSoN infrastructure conceptually surrounds all layers, enabling and govern- ing agent coordination & interaction • All layers are re-shaped based on TuCSoN concepts & metaphors • Agents & Policies sub- layers appear side-by-side, following the TuCSoN approach
  8. 8. The Home Manager platform • Open source platform for Smart Spaces, built on top of the TuCSoN multi-agent infrastructure o deployable also on a Raspberry PI 2 o Java-based (~interoperable with Win10-IoT core) • Smart House immersed in the surrounding environment  Smart Living context o Devices (air conditioners, lights, etc.) o Users of different categories + RBAC • Focus on Context Reasoning & Context Prediction o Satisfy users desires while respecting global constraints  suitable coordination laws to govern interaction o Anticipate needs by exploiting the user’s situation in time and space
  9. 9. Intuitive architecture Main features: o Autonomous “situated” decisions by exploiting the user’s location o Exploration of the environment around the user’s location o Information about the surrounding environment (e.g. weather) o Interaction with selected social networks (e.g. Twitter) o Tracking of the human presence
  10. 10. Smart Environments in HM • Designing a Smart Environment in Home Manager amounts to: o identify relevant device and service categories o define a tuple-based representation of the relevant knowledge o define the agent interaction o develop an agent for each device category & service to interact with Clear separation between • social / individual intelligence • mechanisms / policies Features • independent testing and debug of agents and policies • effective exploitation of the data-driven, multi-paradigm development approach
  11. 11. The Smart Kitchen Case Study
  12. 12. • Smart Fridge & Smart Pantry o food monitoring o collecting historical data on user’s habits o generate the corresponding buy tuple if necessary (policies) • Smart Oven o support the user’s food cooking (e.g. dietary,…) • Smart Mixer o recipe instructions interacting with Smart Fridge & Smart Oven to check food availability  context adaptation • Smart Shopper o predict the user’s needs  make contextualised suggestions o shopping list based on the above data o contact the “proper” vendor based on context- aware policies The Smart Kitchen: scenario
  13. 13. The Smart Kitchen: prototype Middleware  coordination laws  interoperability & integration • Declarative approach o bridge among different forms of heterogeneity o support agent uncoupling o support & promote separation between policies & mechanisms o supports context reasoning
  14. 14. Future (current) work Context prediction & adaptation: prediction agent WEKA Classifier (Ilaria Bertoletti Master's thesis, 15 June 2017) Tempera- ture prefs Device usage policies Action plan on air conditioners Learning & prediction of user habits
  15. 15. Future (current) work Context prediction & adaptation: prediction agent WEKA Classifier (Ilaria Bertoletti Master's thesis, 15 June 2017) CONTEXT PREDICTION • Grab user habits info from multiple sources • Select relevant data • Anticipate user's routine & desires CONTEXT REASONING • Compute heterogeneous context info • Enable HM to make suggestions • Increase HM decision autonomy PROACTIVE ADAPTATION • Autonomously appy action plan on house devices • Enable HM to adapt to new needs • Reduce user's interventions
  16. 16. Future (current) work Context prediction & adaptation: prediction agent WEKA Classifier (Ilaria Bertoletti Master's thesis, 15 June 2017) • Get daily routine • Weather + policies + routine = decision
  17. 17. Future (current) work Context prediction & adaptation: prediction agent WEKA Classifier (Ilaria Bertoletti Master's thesis, 15 June 2017)
  18. 18. Home Manager lays the foundations to support context reasoning and context prediction • Yet, just a starting point.. • A lot of work remains to be done Conclusions (1) Butlers for Smart Spaces • technology-neutral • reference framework for pervasive IoT contexts • focused on users’ situated- ness and interaction aspects Home Manager • concretise the BSS approach • the infrastructure bridges among the agents’ ontologies, APIs, knowledge representations, interaction protocols
  19. 19. Conclusions (2) Future work • Deeper exploration of the context reasoning aspect (machine learning,…) • Cross-platform interoperability • Java/Windows 10 on the Raspberry • Emerging standards • Developing more complex policies and implementing other advanced situated services
  20. 20. Home Manager URLs • Home page http://apice.unibo.it/xwiki/bin/view/Products/HomeManager • Bitbucket repository https://bitbucket.org/tuprologteam/homemanager
  21. 21. Roberta Calegari roberta.calegari@unibo.it Enrico Denti enrico.denti@unibo.it http://www.unibo.it http://www.cse.unibo.it/en http://apice.unibo.it/xwiki/bin/view/Main/?language=en
  22. 22. Prototype screenshots Smart kitchen simulated device vs physical device Mixer agent
  23. 23. Prototype screenshots Smart kitchen cooking requests missing ingredients
  24. 24. Prototype screenshots Smart oven demo implementation
  25. 25. Prototype screenshots Smart fridge demo implementation

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