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Lynggaard Per (Aalborg University Copenhagen, Denmark)
A Distributed Smart Home Artificial Intelligence System
Zeszyty Naukowe Uniwersytetu Szczecińskiego. Ekonomiczne Problemy Usług, 2013, nr 105, s. 521-531, rys., bibliogr. 9 poz.
Tytuł własny numeru
Europejska przestrzeń komunikacji elektronicznej. T. 2
Słowa kluczowe
Dystrybucja, Sztuczna inteligencja, Architektura
Distribution, Artificial intelligence, Architecture
A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more complex system that offer the needed processing capability to support and run more advanced artificial intelligence algorithms.(original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Biblioteka Główna Uniwersytetu Szczecińskiego
Pełny tekst
  1. Bhardwaj S., Ozcelebi T., Lukkien J., Uysal C.: Resource and Service Management Architecture of a Low Capacity Network for Smart Spaces, IEEE Transactions on Consumer Electronics 2012, Vol. 58, No. 2.
  2. Bernheim, Brush A.J.: Home Automation in the Wild: Challenges and Opportunities, ACM Conference on Computer-Human Interaction 2011.
  3. Cook D., Crandall A., Thomas B., Krishnan A.: A Smart Home in a Box, IEEE NCASAS 2012.
  4. Cook D.J.: Learning Setting-Generalized Activity Models for Smart Spaces, IEEE Intelligent Systems 2012, Vol. 27, No. 1.
  5. Gill T., Keller J.M., Anderson D.T., Luke R.H.: A system for change detection and human recognition in voxel space using the Microsoft Kinect sensor, in IEEE, Applied Imagery Pattern Recognition Workshop (AIPR) 2011.
  6. Reinisch C., Kofler M., Kastner W., ThinkHome: A Smart Home as Digital Ecosystem, IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST) 2010.
  7. Sohraby K., Minoli D., Znati T.: Wireless Sensor Networks, Wiley interscience 2007.
  8. Xia L., Chia-Chih Chen, Aggarwal J.K.: Human Detection Using Depth Information by Kinect, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2011.
  9. Ye X., Huang J.: A Framework for Cloud-based Smart Home, International Conference on Computer Science and Network Technology 2011.
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