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A Web System for Managing and Monitoring Smart Environments

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Bioinformatics and Biomedical Engineering (IWBBIO 2016)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9656))

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Abstract

Smart environments have the ability to record information about the behavior of the people by means of their interactions with the objects within an environment. This kind of environments are providing solutions to address some of the problems associated with the growing size and ageing of the population by means of the recognition of activities, monitoring activities of daily living and adapting the environment. In this contribution, a Web system for managing and monitoring smart environments is introduced as an useful tool to activity recognition. The Web system has the advantages to process the information, accessible services and analytic capabilities. Furthermore, a case study monitored by the proposed Web System is illustrated in order to show its performance, usefulness and effectiveness.

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Notes

  1. 1.

    http://ceatic.ujaen.es/es/smart-lab-0.

  2. 2.

    www.tynetec.co.uk.

  3. 3.

    http://sunspotdev.org/.

References

  1. Smith, G., Della Sala, S., Logie, R.H., Maylor, E.A.: Prospective and retrospective memory in normal aging and ementia: a questionnaire study. Memory 8, 311–321 (2000)

    Article  Google Scholar 

  2. Alzheimer’s society. What is dementia? (2013). http://www.alzheimers.org.uk/site/scripts/documents_info.php?documentID=106

  3. Von Strauss, E.: Aging and the occurrence of dementia: findings from a population-based cohort with a large sample of nonagenarians. Arch. Neurol. 56(5), 587–592 (1999)

    Article  Google Scholar 

  4. Holder, L.B., Cook, D.J.: Automated activity-aware prompting for activity initiation. Gerontechnology 11(4), 534–544 (2013)

    Article  Google Scholar 

  5. Feuz, K.D., Cook, D.J., Rosasco, C., Robertson, K., Schmitter-Edgecombe, M.: Automated detection of activity transitions for prompting. IEEE Trans. Hum. Mach. Syst. 45(5), 575–585 (2014)

    Article  Google Scholar 

  6. Das, B., Cook, D.J., Schmitter-Edgecombe, M., Seelye, A.M.: Puck: an automated prompting system for smart environments: toward achieving automated prompting-challenges involved. Pers. Ubiquit. Comput. 16(7), 859–873 (2012)

    Article  Google Scholar 

  7. Cook, D.J., Augusto, J.C., Jakkula, V.R.: Ambient intelligence: technologies, applications, and opportunities. Pervasive Mobile Comput. 5(4), 277–298 (2009)

    Article  Google Scholar 

  8. Chen, L., Hoey, J., Nugent, C., Cook, D.J., Yu, Z.: Sensor-based activity recognition. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42(6), 790–808 (2012)

    Article  Google Scholar 

  9. Synnott, J., Chen, L., Nugent, C.D., Moore, G.: Flexible and customizable visualization of data generated within intelligent environments. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5819–5822, August 2012

    Google Scholar 

  10. Satyanarayanan, M.: Pervasive computing: vision and challenges. IEEE Pers. Commun. 8(4), 10–17 (2001)

    Article  Google Scholar 

  11. Varshney, U.: Pervasive healthcare and wireless health monitoring. Mobile Netw. Appl. 12(2–3), 113–127 (2007)

    Article  Google Scholar 

  12. Emmanouilidis, C., Koutsiamanis, R.-A., Tasidou, A.: Mobile guides: taxonomy of architectures, context awareness, technologies and applications. J. Netw. Comput. Appl. 36(1), 103–125 (2013)

    Article  Google Scholar 

  13. Makris, P., Skoutas, D.N., Skianis, C.: A survey on context-aware mobile and wireless networking: on networking and computing environments’ integration. IEEE Commun. Surv. Tuts. 15(1), 362–386 (2013)

    Article  Google Scholar 

  14. Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Context aware computing for the internet of things: a survey. IEEE Commun. Surv. Tuts. 16(1), 414–454 (2014)

    Article  Google Scholar 

  15. Alam, M.M., Hamida, E.B.: Surveying wearable human assistive technology for life and safety critical applications: standards, challenges and opportunities. Sensors 14(5), 9153–9209 (2014). (Switzerland)

    Article  Google Scholar 

  16. Van Hoof, J., Wouters, E.J.M., Marston, H.R., Vanrumste, B., Overdiep, R.A.: Ambient assisted living and care in The Netherlands: the voice of the user. Int. J. Ambient Comput. Intell. 3(4), 25–40 (2011)

    Article  Google Scholar 

  17. Gu, T., Wang, L., Wu, Z., Tao, X., Lu, J.: A pattern mining approach to sensor-based human activity recognition. IEEE Trans. Knowl. Data Eng. 23(9), 1359–1372 (2011)

    Article  Google Scholar 

  18. Li, C., Lin, M., Yang, L.T., Ding, C.: Integrating the enriched feature with machine learning algorithms for human movement and fall detection. J. Supercomput. 67(3), 854–865 (2014)

    Article  Google Scholar 

  19. Martin, L.A., Pelaez, V.M., Gonzalez, R., Campos, A., Lobato, V.: Environmental user-preference learning for smart homes: an autonomous approach. J. Ambient. Intell. Smart. Environ. 2(3), 327–342 (2010)

    Google Scholar 

  20. Chen, L., Nugent, C.: Ontology-based activity recognition in intelligent pervasive environments. Int. J. Web Inf. Syst. 5(4), 410–430 (2009)

    Article  Google Scholar 

  21. Chen, L., Nugent, C.D., Wang, H.: A knowledge-driven approach to activity recognition in smart homes. IEEE Trans. Knowl. Data Eng. 24(6), 961–974 (2012)

    Article  Google Scholar 

  22. Shah, M., Big data, the internet of things (2015). arXiv preprint arXiv:1503.07092

  23. Maryvonne, M., Bédard, Y., Brisebois, A., Pouliot, J., Marchand, P., Brodeur, J.: Modeling multi-dimensional spatio-temporal data warehouses in a context of evolving specifications. Int. Arch. Photogrammetry Remote Sens. Spat. Inf. Sci. 34(4), 142–147 (2002)

    Google Scholar 

  24. Zaslavsky, A.B., Perera, C., Georgakopoulos, D.: Sensing as a service and big data (2013). CoRR, abs/1301.0159

    Google Scholar 

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Acknowledgements

This contribution has been supported by research projects: UJA2014/06/14 and CEATIC-2013-001.

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Correspondence to Macarena Espinilla .

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Zafra, D., Medina, J., Martinez, L., Nugent, C., Espinilla, M. (2016). A Web System for Managing and Monitoring Smart Environments. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2016. Lecture Notes in Computer Science(), vol 9656. Springer, Cham. https://doi.org/10.1007/978-3-319-31744-1_59

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  • DOI: https://doi.org/10.1007/978-3-319-31744-1_59

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  • Publisher Name: Springer, Cham

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