Dynamic Rule-Based Reasoning in Smart Environments

Viktoriya Degeler

Research output: ThesisThesis fully internal (DIV)

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Smart homes and other types of smart environments can be defined by several important characteristics. The most important is undoubtedly the ability to be context-aware, to sense the physical surroundings and to understand the context of the current situation. Smart environments should be able to reason using this information and to deduce valuable knowledge. They also should have the ability to act intelligently in response to changing situations, according to certain goal criteria. Smart environments are often ubiquitous, which means their sensing and acting capabilities come from devices that are embedded in the physical world.

Most of current commercial smart environment products present only partial solutions, such as automated lighting or energy awareness. Several factors that slow the commercialization of full-scale smart home solutions include the necessity to greatly fine-tune the solution to every new location, the integration and coordination efforts between different components, efforts to keep consistent model across sub-systems that come from different sources, and so on. To summarize, the great amount of efforts that are needed to transfer the solution from one location to another hinders the deployment streamlining possibilities.

What are the commonalities in the design and development process of smart environments? What is an effective approach to design a reasoning engine for smart environments that fulfills all important requirements? How can the effect of sensor errors be minimized with respect to decision making? How can a smart system utilize the existence of diverse energy providers in order to minimize the cost of energy over time? In this thesis we discuss and give answer to these important research questions for current pervasive systems, smart environments in particular.
Translated title of the contributionDynamisch regelgebaseerd redeneren in slimme omgevingen
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Groningen
  • Aiello, Marco, Supervisor
  • Lazovik, Alexander, Co-supervisor
Award date29-Sept-2014
Place of Publication[S.l.]
Print ISBNs978-90-367-7286-0
Electronic ISBNs978-90-367-7285-3
Publication statusPublished - 2014


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