Abstract
Most likely, some of us at least once in his life, has encountered the need to identify a certain type of training, or to improve his physical shape, or even simply to alleviate a condition of physical discomfort. Moreover, nowadays, given the immense technological development and diffusion of so-called wearable sensors, it is also possible to constantly monitor one’s physical conditions both at rest and, above all, during any type of training and then use them as real fitness coaches measuring our performance during a certain exercise and, therefore, establishing our level. It would surely be convenient to have a tool that can help extricate ourselves from the immense variety of existing exercises and that can furthermore recommend a certain type of training deemed most suitable for the user level, his state of health, his preferences on area of the body to train or based on the need to have gymnastic equipment or not.
The main purpose of this work is therefore to create a single ontology, starting from already consolidated ones, thus providing a basis for any future development of intelligent systems for workout recommendations eHealth oriented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Baßçiftçi, F., Incekara, H.: Web based medical decision support system application of CoronaryHeart Disease diagnosis with Boolean functions minimization method. Expert Syst. Appl. 38(11), 14037–14043 (2011)
Cellfie plugin. https://github.com/protegeproject/cellfie-plugin. Accessed 15 October 2020
Cretella, G., Di Martino, B.: A semantic engine for porting applications to the cloud and among clouds. Softw. Pract. Exp. 45(12), 1619–1637 (2015)
Darejeh, A., Pajouh, H.H., Darejeh, A.: An Investigation on the Use of Expert Systems in Developing Web-Based Fitness Exercise Plan Gen10 Beniamino Di Martino and Serena Angela Generator. Article in International Review on Computers and Software, August 2014
Di Martino, B., Esposito, A., Cretella, G.:“Towards a IoT Framework for the Matchmaking of Sensors’ Interfaces”. In: Bourgeois, J. El Baz, D. (ed.) Proceedings - 13th IEEE International Conference on Ubiquitous Intelligence and Computing (2017), pp. 888–894 (2017)
Di Martino, B., Esposito, A., Liguori, S., Ospedale, F., Maisto, S.A., Nacchia, S.: A fuzzy prolog and ontology driven framework for medical diagnosis using IoT devices. In: Terzo, O., Barolli, L. (eds.) Complex, Intelligent, and Software Intensive Systems. CISIS 2017. Advances in Intelligent Systems and Computing, vol. 611. Springer, Cham (2018). ISSN 21945357. https://doi.org/10.1007/978-3-319-61566-0_83
Di Martino, B., Esposito, A., Maisto, S.A. and Nacchia, S.: “A semantic IoT framework to support RESTful devices’ API interoperability”. In: Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017, pp. 78–83 (2017)
Di Martino, B., Posillipo, A., Nacchia, S. and Maisto, S.A.: “A Q&A tool to produce an Ad-Hoc OpenAPI specification to identify equivalent REST Api Services”. In: Proceedings - 2018 IEEE International Conference on Smart Computing, SMARTCOMP 2018, pp. 375–380 (2018)
Di Martino, B., Rak, M., Ficco, M., Esposito, A., Maisto, S., Nacchia, S.: Internet of things reference architectures, security and interoperability: a survey. Internet Things 1–2, 99–112 (2018)
Dogdu, E.: Semantic Web in eHealth. TOBB University of Economics and Technology, Ankara, Turkey (2009)
Foust, J.C.: Ontology of Physical Exercises. https://bioportal.bioontology.org/ontologies/OPE. Accessed 15 October 2020
Haller, A., Janowicz, K., Cox, S., Le Phuoc, D., Taylor, K., Lefrançois, M.: Semantic Sensor Network Ontology. https://www.w3.org/TR/vocab-ssn/. Accessed 15 October 2020
Horn, G., et al.: An architecture for using commodity devices and smart phones in health systems. In: 2016 IEEE Symposium on Computers and Communication (ISCC), pp. 255–260 (2016)
Jackson, P.: Introduction to Expert Systems, 3rd edn. Addison Wesley, Boston (1998)
Jefit. https://www.jefit.com/exercises/. Accessed 15 October 2020
Di Martino, B., Li, K.-C., Yang, L.T., Esposito, A.: Internet of Everything, pp. 1–231. Springer, Singapore (2018)
Protégé software. https://protege.stanford.edu/. Accessed 15 October 2020
Schriml, L.: Human Disease Ontology. https://disease-ontology.org/. Accessed 15 October 2020
Web Scraper. https://webscraper.io/. Accessed 15 October 2020
Yang, L.T., Di Martino, B., Zhang, Q.: “Internet of Everything”. In: Mobile Information Systems 2017 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Di Martino, B., Gracco, S.A. (2021). Semantic Techniques for IoT Sensing and eHealth Training Recommendations. In: Barolli, L., Yim, K., Enokido, T. (eds) Complex, Intelligent and Software Intensive Systems. CISIS 2021. Lecture Notes in Networks and Systems, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-030-79725-6_63
Download citation
DOI: https://doi.org/10.1007/978-3-030-79725-6_63
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-79724-9
Online ISBN: 978-3-030-79725-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)