Abstract
Ambient Intelligence is growing phenomena caused by advances of speed and size of computational hardware. It is possible to collect data from various sensors, devices or services and react to evaluated event and start the predefined process. These systems are closely connected with Cloud based services as they provide publicly available interface for management and visualization, computational and storage capabilities for forecasts and other advanced data processing to create ambient intelligence environment. The true ambient environments react to the presence of people and the sensors and actuators have become part of the environment.
This article presents RoboPhery project aimed to provide abstraction layer for interfacing any low cost hardware sensors and actuators with MQTT and Time-series Database bindings, that can serve as sensory network for Ambient Intelligence environments. The service architecture is designed to be so simple at hardware level to support single-board micro-controllers like ESP2866, ESP32 modules as well as single-board computers based on ARM or x86 architectures. The communication among individual devices is handled by the standard MQTT messages. The same devices can be configured to support multiple use-cases on configuration level to lower the operational costs of the solution.
This is a preview of subscription content, log in via an institution to check access.
References
Aarts, E., Encarnao, J.L.: True Visions: The Emergence of Ambient Intelligence. Springer, Heidelberg (2006)
Aarts, E., Harwig, R., Schuurmans, M.: Ambient Intelligence in The Invisible Future, pp. 235–250. McGraw-Hill Inc. (2002)
Arribas-Ayllon, M.: Ambient Intelligence: an innovation narrative, 16 April 2017. http://www.academia.edu/1080720/Ambient_Intelligence_an_innovation_narrative
Augusto, J.C., Nugent, C.D.: A new architecture for smart homes based on ADB and temporal reasoning. In: Proceedings of 2nd International Conference on Smart Homes and Health Telematic, ICOST 2004, pp. 106–113 (2005)
Bielikova, M., Krajcovic, T.: Ambient Intelligence within a Home Environment, 12 April 2017. https://www.ercim.eu/publication/Ercim_News/enw47/bielikova.html
Dunning, T., Friedman, E., Loukides, M.K., Demarest, R.: Time Series Databases: New Ways to Store and Access Data. O’Reilly Media, Sebastopol (2014)
Foster, I., Kesselman, C., Nick, J.M., Tuecke, S.: Grid services for distributed system integration. Computer 35(6), 37–46 (2002)
Ha, Y., Sohn, J., Cho, Y., Yoon, H.: A robotic service framework supporting automated integration of ubiquitous sensors and devices. Inf. Sci. 177, 657–679 (2007)
Horálek, J., Matyska, J., Stepan, J., Vancl, M., Cimler, R., Sobĕslav, V.: Lower layers of a cloud driven smart home system. In: Barbucha, D., Nguyen, N.T., Batubara, J. (eds.) New Trends in Intelligent Information and Database Systems. SCI, vol. 598, pp. 219–228. Springer, Cham (2015). doi:10.1007/978-3-319-16211-9_23
Huhns, M., Singh, M.P.: Service-oriented computing: key concepts and principles. IEEE Internet Comput. 9(1), 75–81 (2005)
Lampkin, V., Tat Leong, W., Olivera, L., Rawat, S., Subrahmanyam, N., Xiang, R.: Building Smarter Planet Solutions with MQTT and IBM WebSphere MQ Telemetry. An IBM Redbooks Publication (2012)
Li, S., Xu, L.D., Zhao, S.: The internet of things: a survey. Inf. Syst. Front. 17(2), 243–259 (2015)
Mani Chandy, K.: Event-Driven Applications: Costs, Benefits and Design Approaches (2006)
Papazoglou, M.P.: Service -oriented computing: concepts, characteristics and directions. In: Proceedings - 4th International Conference on Web Information Systems Engineering, WISE 2003, pp. 3–12 (2003)
Papazoglou, M.P., Van Den Heuvel, W.J.: Service oriented architectures: approaches, technologies and research issues. VLDB J. 16(3), 389–415 (2007)
Preuveneers, D., Van den Bergh, J., Wagelaar, D., Rigole, P., Clarckx, T., Berbers, Y., Coninx, K., Jonckers, V., De Bosschere, K.: Towards an extensible context ontology for ambient intelligence. In: Ambient Intelligence: Second European Symposium, EUSAI 2004, pp. 148–159 (2004)
Rui, C., Yi-bin, H., Zhang-qin, H., Jian, H.: Modeling the ambient intelligence application system: concept, software, data, and network. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 39, 299–314 (2009)
Sobeslav, V., Horalek, J.: Communications and quality aspects of smart grid network design. In: Wong, W.E. (ed.) Proceedings of the 4th International Conference on Computer Engineering and Networks, vol. 355, pp. 1255–1262. Springer, Cham (2015). doi:10.1007/978-3-319-11104-9_143
Wu, D., Rosen, D.W., Wang, L., Schaefer, D.: Cloud-based design and manufacturing: a new paradigm in digital manufacturing and design innovation. CAD Comput. Aided Des. 59, 1–14 (2015)
Zelkha, E., Epstein, B., Birrel, S., Dodsworth, C.: From devices to “Ambient Intelligence”. Digital Living Room Conference (1988)
Acknowledgement
This work and the contribution were also supported by project of specific science, Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Komarek, A., Pavlik, J., Mercl, L., Sobeslav, V. (2017). Hardware Layer of Ambient Intelligence Environment Implementation. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-67077-5_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67076-8
Online ISBN: 978-3-319-67077-5
eBook Packages: Computer ScienceComputer Science (R0)