Abstract
An architecture capable of monitoring biophysical parameters from both the human, veterinary, and environmental domains is described, which focuses on the intersection of Internet of Things (IoT) and Edge Computing. The main features of the architecture - pluggability, cross-referenceability, and measures accuracy and reliability - were developed to deal with the characteristics of the One Digital Health framework. The potential benefits of a pluggable and referenceable architecture have been emphasized for different kinds of stakeholders, as described in two different use-cases from the human/animal and the environmental domains. Potential benefits for the stakeholders from deploying the architecture compared to market and applied research solutions have been discussed.
O. Tamburis and A. Tramontano—Share first co-authorship.
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References
Lampropoulos, G., Siakas, K., Anastasiadis, T.: Internet of things in the context of industry 4.0: an overview. Int. J. Entrepre. Knowl. 7, 4–19 (2019)
Umair, M., Cheema, M.A., Cheema, O., Li, H., Lu, H.: Impact of COVID-19 on IoT adoption in healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Sensors 21, 3838 (2021)
Wilkes, M., et al.: One Health workers: innovations in early detection of human, animal, and plant disease outbreaks. J. Glob. Health Rep. 3, e2019093 (2019)
Benis, A., Tamburis, O., Chronaki, C., Moen, A.: One digital health: a unified framework for future health ecosystems. J. Med. Internet Res. 23, e22189–e22189 (2021). https://doi.org/10.2196/22189
Benis, A., Haghi, M., Deserno, T.M., Tamburis, O.: One digital health intervention for monitoring human and animal welfare in smart cities: viewpoint and use case. JMIR Med. Inform. 11, e43871–e43871 (2023). https://doi.org/10.2196/43871
Tamburis, O., Magliulo, M., Tramontano, A., Perillo, G., Benis, A., Calabrò, S.: Precision grazing: when agriculture, livestock and technology unite. In: 2023 IEEE International Conference on Big Data (BigData), pp. 3510–3515. IEEE (2023)
Cisco: Annual Internet Report (201832023) (2020)
Reinsel, D., Gantz, J., Rydning, J.: The digitization of the world - from edge to core. International Data Corporation (2018)
Hayyolalam, V., Aloqaily, M., Ozkasap, O., Guizani, M.: Edge-assisted solutions for IoT-based connected healthcare systems: a literature review. IEEE Internet Things J. 9, 9419–9443 (2022). https://doi.org/10.1109/JIOT.2021.3135200
Angelucci, A., Kuller, D., Aliverti, A.: A home telemedicine system for continuous respiratory monitoring. IEEE J. Biomed. Health Inf. 25, 1247–1256 (2021). https://doi.org/10.1109/JBHI.2020.3012621
Singh, P.: Internet of Things based health monitoring system: opportunities and challenges. Int. J. Adv. Res. Comput. Sci. 9, 224–228 (2018). https://doi.org/10.26483/ijarcs.v9i1.5308
abdulmalek, s., et al.: iot-based healthcare-monitoring system towards improving quality of life: a review. Healthcare (Basel) 10, 1993 (2022). https://doi.org/10.3390/healthcare10101993
Tramontano, A., Tamburis, O., Cioce, S., Venticinque, S., Magliulo, M.: Heart rate estimation from ballistocardiogram signals processing via low-cost telemedicine architectures: a comparative performance evaluation. Front. Digital Health 5, 1222898 (2023)
Yacchirema, D., De Puga, J.S., Palau, C., Esteve, M.: Fall detection system for elderly people using IoT and Big Data. Procedia Comput. Sci. 130, 603–610 (2018). https://doi.org/10.1016/j.procs.2018.04.110
Vega-Barbas, M., Diaz-Olivares, J.A., Lu, K., Forsman, M., Seoane, F., Abtahi, F.: P-ergonomics platform: toward precise, pervasive, and personalized ergonomics using wearable sensors and edge computing. Sensors (Basel) 19, 1225 (2019). https://doi.org/10.3390/s19051225
Ireifej, S.J., Krol, J.: Case studies of fifteen novel species successfully aided with the use of a veterinary teletriage service. Front. Veter. Sci. 10 (2023)
Tamburis, O., Masciari, E., Fatone, G.: Development of a decision tree model to improve case detection via information extraction from veterinary electronic medical records. In: Proceedings (2021). http://ceur-ws.org. ISSN. 1613-0073
Tramontano, A., Tamburis, O., Magliulo, M.: To the Green from the Bl(u)e: an innovative system for monitoring urban green areas. In: 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pp. 646–650. IEEE (2022)
Luzi, D., Pecoraro, F., Tamburis, O.: Appraising healthcare delivery provision: a framework to model business processes. In: Informatics for Health: Connected Citizen-Led Wellness and Population Health, pp. 511–515. IOS Press (2017)
Liu, C., Zhang, Y., Zhou, H.: A comprehensive study of bluetooth low energy. In: Journal of Physics: Conference Series, p. 012021. IOP Publishing (2021)
Koutalieris, G., et al.: Enhancing urban environmental sustainability through unified stakeholders needs co-creation process (AENEA). In: 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pp. 899–904. IEEE, Milano (2023). https://doi.org/10.1109/MetroXRAINE58569.2023.10405595
Tamburis, O., Benis, A.: One digital health for more FAIRness. Methods Inf. Med. 61, e116–e124 (2022). https://doi.org/10.1055/a-1938-0533
Wilkinson, M.D., et al.: The FAIR Guiding principles for scientific data management and stewardship. Sci. Data 3, 1–9 (2016)
Motta, C., et al.: A framework for FAIR robotic datasets. Sci. Data 10, 620 (2023)
Benis, A., et al.: Medical informatics and digital health multilingual ontology (MIMO): a tool to improve international collaborations. Int. J. Med. Informat. 167, 104860 (2022)
Benis, A., Tamburis, O.: The need for green and responsible medical informatics and digital health: looking forward with one digital health. Yearb. Med. Inf. 32, 007–009 (2023). https://doi.org/10.1055/s-0043-1768717
OneAquaHealth Project Website. https://www.oneaquahealth.eu/. Accessed 02 Feb 2024
Acknowledgments
The research was partially funded by the European Union’s Horizon Europe Research and Innovation Program (HORIZON-CL6- 2022-GOVERNANCE-01) under grant agreement No. 101086521 - OneAquaHealth (Protecting urban aquatic ecosystems to promote One Health).
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Tamburis, O., Tramontano, A., Perillo, G., Benis, A., Magliulo, M. (2024). All for One, All at Once: A Pluggable and Referenceable Architecture for Monitoring Biophysical Parameters Across Intertwined Domains. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-031-57931-8_26
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