HealthDash: Remote monitoring of patients using programming based on data flow
Abstract
In this paper, we propose HealthDash, a framework for developing IoT solutions for health care. HealthDash employs the data-flow-oriented pro- gramming paradigm, from the cloud layer to the network edge (fog layer), unifying development technologies across layers, that is, from edge devices to decision making. We conducted an experiment to evaluate the proposal with the simulation of the transmission of data collected from home-monitored pati- ents with chronic diseases. In the simulation, we observed the performance of the two implemented solutions to both continuous and event-based scenarios of data transmission. The results showed that HealthDash solution provides flexi- ble infrastructure, consuming less bandwidth and spending little response time.
References
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Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., and Liljeberg, P. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78:641–658. http://dx.doi.org/10.1016/j.future.2017.02.014
Sousa, T. B. (2012). Dataflow Programming Concept, Languages and Applications. Doctoral Symposium on Informatics Engineering, 7(November):13.
Ahmad, M., Amin, M. B., Hussain, S., Kang, B. H., Cheong, T., and Lee, S. (2016). Health Fog: a novel framework for health and wellness applications. The Journal of Supercomputing, 72(10):3677–3695. http://dx.doi.org/10.1007/s11227-016-1634-x
Cerina, L., Notargiacomo, S., Paccanit, M. G., and Santambrogio, M. D. (2017). A fog-computing architecture for preventive healthcare and assisted living in smart ambients. Proc. Int. Forum on Research and Technologies for Society and Industry - RTSI 2017. http://dx.doi.org/10.1109/RTSI.2017.8065939
Farahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., and Mankodiya, K. (2018). Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare. Future Generation Computer Systems, 78:659–676. http://dx.doi.org/10.1016/j.future.2017.04.036
Gia, T. N., Jiang, M., Rahmani, A. M., Westerlund, T., Liljeberg, P., and Tenhunen, H. (2015). Fog computing in healthcare Internet of Things: A case study on ECG feature extraction. Proceedings of the CIT 2015, pages 356–363. http://dx.doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.51
Giang, N. K., Blackstock, M., Lea, R., and Leung, V. C. (2015). Developing IoT applications in the Fog: A Distributed Dataflow approach. Proceedings - 2015 5th International Conference on the Internet of Things, IoT 2015, (January 2016):155–162. http://dx.doi.org/10.1109/IOT.2015.7356560
Gupta, H., Vahid Dastjerdi, A., Ghosh, S. K., and Buyya, R. (2017). iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments. Software: Practice and Experience, 47(9):1275–1296. http://dx.doi.org/10.1002/spe.2509
Hong, K., Lillethun, D., Ramachandran, U., Ottenwälder, B., and Koldehofe, B. (2013). Mobile fog: a programming model for large-scale applications on the internet of things. In Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing - MCC ’13, page 15, New York, New York, USA. ACM Press. http://dx.doi.org/10.1145/2491266.2491270
Liu, L., Stroulia, E., Nikolaidis, I., Miguel-Cruz, A., and Rios Rincon, A. (2016). Smart homes and home health monitoring technologies for older adults: A systematic review. International Journal of Medical Informatics, 91:44–59. http://dx.doi.org/10.1016/j.ijmedinf.2016.04.007
Malik, B. H., Cheema, S. N., Iqbal, I., Mahmood, Y., Ali, M., and Mudasser, A. (2018). From Cloud Computing to Fog Computing ( C2F ): The key technology provides services in health care big data. 03010. http://dx.doi.org/10.1051/matecconf/201818903010
Pare, G., Jaana, M., and Sicotte, C. (2007). Systematic Review of Home Telemonitoring for Chronic Diseases: The Evidence Base. Journal of the American Medical Informatics Association, 14(3):269–277. http://dx.doi.org/10.1197/jamia.M2270
Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., and Liljeberg, P. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78:641–658. http://dx.doi.org/10.1016/j.future.2017.02.014
Sousa, T. B. (2012). Dataflow Programming Concept, Languages and Applications. Doctoral Symposium on Informatics Engineering, 7(November):13.
Published
2019-06-11
How to Cite
CELESTRINI, Jordano R.; ROCHA, Renato N.; SANTOS, Celso A. S.; MOTA, Vinícius F. S. ; FILHO, José G. Pereira; ANDREÃO, Rodrigo V..
HealthDash: Remote monitoring of patients using programming based on data flow. In: BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTH (SBCAS), 19. , 2019, Niterói.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 222-233.
ISSN 2763-8952.
DOI: https://doi.org/10.5753/sbcas.2019.6256.
