Skip to main content
Log in

System architecture using human interaction markup language for context awareness in home network

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

As pervasive computing is developed, a user's context information will be used in a system to provide the user with intelligent services. Context is defined as information that characterizes the situation of an entity under a certain system environment. In this paper, we classify the context in a system into three types: user context, device context, and proximity context, which is the context information between a user and device. We designed HIML (Human Interaction Markup Language) to express the proposed contexts, and the middleware performed on various platforms, including a NUI/NUX (Natural User Interface/Natural User eXperience) platform, and interacted between appliances and sensors using HIML. We demonstrated its functions through experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Augusto JC, Callaghan V, Cook D, Kameas A, Satoh I (2013) Intelligent environments: a manifesto. Human-centric Computing and Information Sciences 3(1):1–18. doi:10.1186/2192-1962-3-12

    Article  Google Scholar 

  2. Dey AK, Abowd GD (1999) Towards a better understanding of context and context-awareness. Technical Report GIT-GVU-99-22, Georgia Institute of Technology College of Computing.

  3. DEY AK, Abowd GD, Salber D (2001) A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum Comput Interact 16(2):97–166. doi:10.1207/S15327051HCI16234_02

    Article  Google Scholar 

  4. Dubey T, Sahu OP (2013) Self-localized packet forwarding in wireless sensor networks. Journal of Information Processing Systems 9(3):477–488. doi:10.3745/JIPS.2013.9.3.477

    Article  Google Scholar 

  5. Hong S, Chang J (2013) A new k-NN query processing algorithm based on multicasting-based cell expansion in location-based services. Journal of Convergence 4(4):1–6

    Article  MathSciNet  Google Scholar 

  6. Hong JI, Landay JA (2001) An infrastructure approach to context-aware computing. Hum Comput Interact 16(2):287–303. doi:10.1207/S15327051HCI16234_11

    Article  Google Scholar 

  7. Korpipaa P, Mantyjarvi J, Kela J, Keranen H, Malm EJ (2003) Managing context information in mobile devices. IEEE pervasive computing 2(3):42–51. doi:10.1109/MPRV.2003.1228526

    Article  Google Scholar 

  8. Lee H, Chung K, Jhang K (2013) A study of wireless sensor network routing protocols for maintenance access hatch condition surveillance. Journal of Information Processing Systems 9:237–246. doi:10.3745/JIPS.2013.9.2.237

    Article  Google Scholar 

  9. Lee G, Shin D, Shin D (2013) An implementation of intuitive NUI/NUX conversion framework using kinect and XML. Proceedings of the FTRA 2013 International Symposium on Ubiquitous Computing and Embedded Systems 160–164

  10. Luo Y, Hoeber O, Chen Y (2013) Enhancing Wi-Fi fingerprinting for indoor positioning using human-centric collaborative feedback. Human-centric Computing and Information Sciences 3(1):1–23. doi:10.1186/2192-1962-3-2

    Article  Google Scholar 

  11. McNaull J, Augusto JC, Mulvenna M, McCullagh P (2014) Flexible context aware interface for ambient assisted living. Human-centric Computing and Information Sciences 4(1):1. doi:10.1186/2192-1962-4-1

    Article  Google Scholar 

  12. Ng CK, Ee GK, Noordin NK (2013) Finger triggered virtual musical instruments. Journal of Convergence 4(1):39–46

    Google Scholar 

  13. Peng K (2013) A secure network for mobile wireless service. Journal of Information Processing Systems 9(2):247–258. doi:10.3745/JIPS.2013.9.2.247

    Article  Google Scholar 

  14. Rose B (2001) Home networks: a standards perspective. IEEE Commun Mag 39(12):78–85. doi:10.1109/35.968816

    Article  Google Scholar 

  15. Shafer SAN, Brumitt B, Cadiz JJ (2001) Interaction issues in context-aware intelligent environments. Human-Computer Interaction Journal 16(2):363–378. doi:10.1207/S15327051HCI16234_16

    Article  Google Scholar 

  16. Weiser M (1993) Some computer science issues in ubiquitous computing. Commun ACM 36(7):75–84

    Article  Google Scholar 

  17. Yoon M, Chang J, Kim Y (2013) An energy-efficient routing protocol using message success rate in wireless sensor networks. Journal of Convergence 4(1):15–22

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2013-H0301-13-4007) supervised by the NIPA (National IT Industry Promotion Agency).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dongkyoo Shin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shin, D., Lee, G., Shin, D. et al. System architecture using human interaction markup language for context awareness in home network. Multimed Tools Appl 75, 15199–15209 (2016). https://doi.org/10.1007/s11042-014-2286-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-014-2286-6

Keywords

Navigation