Empowering IoT Healthcare Solutions with Enhanced Flexibility and Efficiency
DOI:
https://doi.org/10.32628/IJSRSET2411114Keywords:
Internet of Things( IoT ),Cloud Computing(CC),Fog Computing,HealthDash.Abstract
This research proposes a architecture called HealthDash for developing Internet of Things (IoT) solutions in healthcare. The main Aim of this research is to over come the complexity problems in creating and keeping up with computational health solutions with increased flexibility, where scenarios are often complex and dynamic. HealthDash aims to unify technologies at both the fog and cloud layers, providing dynamism in creating IoT applications and reducing data transmission between these layers. To specify which layer (fog or cloud) data flows will be executed, the suggested approach makes use of the data flow-oriented programming paradigm, empowers IoT healthcare solutions with greater flexibility, efficiency,and privacy.The architecture aims to simplify the creation and maintenance of computational solutions in the complex and dynamic healthcare domain. HealthDash is designed to address challenges such as low latency, data transmission efficiency, and privacy concerns in remote patient monitoring scenarios.Enabling dynamic creation of IoT applications in both fog and cloud layers. Reducing data transmission between fog and cloud layers. Utilizing a unified data flow-oriented programming paradigm.
References
- Levina, P. Kaliyamoorthi, Vinjamuri S.N.CH. Dattu, G Dineshnath, S. Jaiganesh, Dinesh Chandra Dobhal, C. R. Rene Robin. "A Novel Architecture for Developing IoT Solutions Applied to Healthcare", 2023 2nd International Conference on Applied Arti?cial Intelligence and Computing (ICAAIC), 2023 Publication
- Aazam, M. and Huh, E. N. (2015). E-HAMC: Leveraging Fog computing for emergency alert service. In 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2015, pages 518–523. IEEE.
- 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.
- Hong, K., Lillethun, D., Ramachandran, U., Ottenwa¨lder, 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 computingMCC ’13, page 15, New York, New York, USA. ACM Press.
- Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., and Lilje- berg, 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.
- Gupta, H., VahidDastjerdi, 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.
- Sousa, T. B. (2012). Dataflow Programming Concept, Languages and Applications. Doc- toral Symposium on Informatics Engineering, 7(November):13.
- 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.
- 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.
- Giang, N. K., Blackstock, M., Lea, R., and Leung, V. C. (2015). Developing IoTapplicati- ons in the Fog: A Distributed Dataflow approach. Proceedings - 2015 5th International Conference on the Internet of Things, IoT 2015, (January 2016):155–162.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET
This work is licensed under a Creative Commons Attribution 4.0 International License.