Abstract
With the advance in the Internet of Things (IoT), new ways of acquiring, processing, and managing collected data from electronic devices are being developed to provide support for more complex systems. This process of transforming the acquired data from the physical world, through the sensors, into viable information on which the applications can make decisions upon, must consider the various implementation scenarios and the business and technical requirements, such as security, privacy, and interoperability between heterogeneous devices (which often communicate using different protocols and require a common vocabulary). With the increasing complexity of these requirements, it becomes urgent to develop an infrastructure to handle the associated processes and provide a middle ground layer on which the physical and digital world are connected and translated into each other. This software layer, or middleware, can be described as a hub and aims to fill the gap between devices and information systems. This work contributes with a study of mechanisms and methodologies for the collection of data, interoperability of systems and data filtering, to optimize and automate, using a lightweight approach, and the collection and pre-analysis of the data to be used by the various applications of the IoT systems, such as the SME manufacturing industries.
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References
Rose, J., Eldridge, S., & Chaplin, L. (2015). The internet of things: An overview—Understanding the issues and challenges of a more connected world. Internet Soc.
Lopes, F., Ferreira, J., Jardim-Goncalves, R., & Agostinho, C. (2017). Semantic maps for IoT network reorganization in face of sensor malfunctioning.
Agostinho, C., Sarraipa, J., Goncalves, D., Jardim-Goncalves, R. (2011). Tuple-based semantic and structural mapping for a sustainable interoperability. In IFIP Advances in Information and Communication Technology.
Huang, Y., & Li, G. (2010). Descriptive models for Internet of things. In Proceedings of 2010 International Conference on Intelligent Control and Information Processing.
Rosenblum, D.S. (2001) Interoperability and middleware (pp. 1–5).
C2NET: C2NET Project. http://c2net-project.eu/.
Ojha, S., & Bandil, P. L. (2016). IoT based data acquisition system using Raspberry Pi.
Fersi, G. (2015). Middleware for internet of things: A study. In Proceedings—IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS.
Fox, P. (2011). Data management considerations for the data life cycle. NRC STS.
Pietschmann, S., Mitschick, A., Winkler, R., & Meißner, K. (2008). CROCO: ontology-based, cross-application context management, SMAP 2008.
Chen, H., Finin, T., Joshi, A., Kagal, L., Perich, F., & Chakraborty, D. (2004). Meet the Semantic web in smart spaces. IEEE Internet Comput, 8, 69–79.
Salman, T., & Jain, R. (2017). Networking protocols and standards for internet of things. In Internet of Things and Data Analytics Handbook (pp. 215–238).
Han, J., Kamber, M., & Pei, J. (2012). Data mining: Concepts and techniques.
Chaqfeh, M. A., & Mohamed, N. (2012) Challenges in middleware solutions for the internet of things. In Proceedings of 2012 International Conference on Collaboration Technologies Systems CTS 2012.
Gómez-Goiri, A., & López-De-Ipiña, D. (2010). A triple space-based semantic distributed middleware for internet of things. In Lecture Notes in Computer Science.
Katasonov, A., Kaykova, O., Khriyenko, O., Nikitin, S., & Terziyan, V. (2008). Smart semantic middleware for the internet of things (pp. 169–178). ICINCO-ICSO.
Luckenbach, T., Gober, P., Arbanowski, S., Kotsopoulos, A., & Kim, K. (2005). TinyREST: A protocol for integrating sensor networks into the internet. In Proceedings of REALWSN.
Mozzaquatro, B. A., Jardim-Goncalves, R., Melo, R., & Agostinho, C. (2016). The application of security adaptive framework for sensor in industrial systems. In SAS 2016.
Adolphs, P., Bedenbender, H., Dirzus, D., Ehlich, M., Epple, U., Hankel, M., Heidel, R., Hoffmeister, M., Huhle, H., Kärcher, B., Koziolek, H., Pichler, R., Pollmeier, S., Schewe, F., Walter, A., Waser, B., & Wollschlaeger, M. (2015) RAMI Industrie 4.0.
Acknowledgements
The research leading to these results has received funding from the EC HORIZON2020 Program under grant agreement n° C2NET 636909 (http://www.c2net-project.eu/) and nº VF-OS 723710 (http://vf-os.eu/), and from Faculty of Science and Technology of Nova University of Lisbon.
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Agostinho, C., Lopes, F., Ferreira, J., Ghimire, S., Marques, M. (2019). A Lightweight IoT Hub for SME Manufacturing Industries. In: Popplewell, K., Thoben, KD., Knothe, T., Poler, R. (eds) Enterprise Interoperability VIII. Proceedings of the I-ESA Conferences, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-030-13693-2_31
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DOI: https://doi.org/10.1007/978-3-030-13693-2_31
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