Human integration in an ontology-based IoT system

• Autorzy: Skarżyński Kamil , Bartyna Waldemar , Stępniak Marcin

Identyfikatory

DOI

10.34739/si.2020.24.04

• Języki publikacji: EN

Abstrakty

EN

The IoT systems are growing field of automation. In contrast to industrial applications, where the system is custom made for each customer or use case, the home IoT systems can be composed and used in many, sometimes dangerous and unpredictable, ways. This paper presents a system that is based on a common ontology as a unified and universal method of representing the environment including humans. Such approach allows for easy integration of heterogenous devices and declarative definition of services, tasks, and rules ensuring human safety and/or comfort.

Słowa kluczowe

EN

IoT; ontology; multi-robot systems; smart environment

• Wydawca: Wydawnictwo Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach
• Czasopismo: Studia Informatica : systems and information technology
• Rocznik: 2020
• Tom: Vol. 1-2(24)
• Strony: 53--69
• Opis fizyczny: Bibliogr. 20 poz., rys.

Twórcy

autor

Skarżyński Kamil

• Siedlce University of Natural Sciences and Humanities, Faculty of Exact and Natural Sciences, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland

autor

Bartyna Waldemar

• Siedlce University of Natural Sciences and Humanities, Faculty of Exact and Natural Sciences, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland

autor

Stępniak Marcin

• Siedlce University of Natural Sciences and Humanities, Faculty of Exact and Natural Sciences, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland

Bibliografia

• 1. Celik Z. B., Tan G., McDaniel P.: IoTGuard: Dynamic Enforcement of Security and Safety Policy in Commodity IoT. In Proceedings Network and Distributed System Security Symposium. Internet Society, San Diego, CA, 2019.
• 2. IFTTT (if this, then that): Helps your apps and devices work together. (https://ifttt.com/, access date: 01.10.2020).
• 3. Ferry N., Nguyen P., Song H., Novac P. E., Lavirotte S., Tigli J. Y., Solberg A.: GeneSIS: Continuous Orchestration and Deployment of Smart IoT Systems. In IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), pp. 870-875. IEEE, Milwaukee, USA, 2019 (https://ieeexplore.ieee.org/document/8753981/).
• 4. Liu R., Wang Z., Garcia L., Srivastava M.: Remedio T: Remedial Actions for Internet-of-Things Conflicts. In Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 101-110. ACM, New York, USA, 2019.
• 5. Samsung Smart things, Smart home. Intelligent living. (https://www.smartthings.com/, access date: 01.10.2020).
• 6. Samsung Smart things. Developer documentation. (http://docs.smartthings.com/en/latest, access date: 01.10.2020).
• 7. IDEAL (Project), ScienceDirect (Service en ligne): Knowledge acquisition. London: Academic Press, 1993 (http://www.sciencedirect.com/science/journal/10428143, access date: 01.10.2020).
• 8. Skarzynski K., Stepniak M., Bartyna W., Ambroszkiewicz S.: SO-MRS: A Multi-robot System Architecture Based on the SOA Paradigm and Ontology. In M. Giuliani, T. Assaf, M. E. Giannaccini (editors), Towards Autonomous Robotic Systems, pp. 330-342. Springer International Publishing, Cham, 2018.
• 9. TRADFRI - Smart Home Products - Lighting, Wi-Fi Speakers, Blinds. (https://www.ikea.com/us/en/cat/smart-home-hs001/, access date: 01.10.2020).
• 10. TRADFRI - C# integration. (https://github.com/tomidix/CSharpTradFriLibrary, access date: 01.10.2020).
• 11. Node-RED. (https://nodered.org/, access date: 01.10.2020).
• 12. Home Assistant. (https://www.home-assistant.io/, access date: 01.10.2020).
• 13. FIBARO | Smart Home. (https://www.fibaro.com/pl/, access date: 01.10.2020).
• 14. Xiaomi Mi Smart Home - category of Xiaomi smart devices and accessories for it. (https://xiaomi-mi.com/mi-smart-home/, access date: 01.10.2020).
• 15. Hassija V., Chamola V., Saxena V., Jain D., Goyal P., Sikdar B.: A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures. IEEE Access, vol. 7, 2019 (https://ieeexplore.ieee.org/document/8742551).
• 16. Gartner Special Report. (https://www.gartner.com/en/newsroom/press-releases/2014-09-08-gartner-says-a-typical-family-home-could-contain-more-than-500-smart-devices-by-2022, access date: 01.10.2020)
• 17. Redmon J., Divvala S., Girshick R., Farhadi A.: You Only Look Once: Unified, Real-Time Object Detection. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779-788. Las Vegas, USA, 2016.
• 18. Parkhi O. M., Vedaldi A., Zisserman A.: Deep Face Recognition. In Procedings of the British Machine Vision Conference 2015, pp. 41.1-41.12. British Machine Vision Association, Swansea, 2015.
• 19. Ng H. W., Winkler S.: A data-driven approach to cleaning large face datasets. In IEEE International Conference on Image Processing (ICIP), pp. 343-347. Paris, France, 2014.
• 20. Face recognition library. (https://github.com/ageitgey/face_recognition, access date: 01.10.2020).