Hybrid Data Compression System In Smart E-Health Gateway For Medical Monitoring Applications
International Journal of Computer Science and Engineering |
© 2020 by SSRG - IJCSE Journal |
Volume 7 Issue 1 |
Year of Publication : 2020 |
Authors : Mezui Eya’a Guy Lysmos, Dr.Mostafa Hanoune |
How to Cite?
Mezui Eya’a Guy Lysmos, Dr.Mostafa Hanoune, "Hybrid Data Compression System In Smart E-Health Gateway For Medical Monitoring Applications," SSRG International Journal of Computer Science and Engineering , vol. 7, no. 1, pp. 1-6, 2020. Crossref, https://doi.org/10.14445/23488387/IJCSE-V7I1P101
Abstract:
161 millions healthcare devices will be connected by 2020 worldwide [1], which represents a real big data challenge, to store and process all medical data with the necessary historical depth. This is why we operate strategically in this article, one of the main services of the smart gateway, which is data compression to implement a hybrid data compression system for medical surveillance applications. It is by considering many challenges, both in terms of energy efficiency and security, which we effectively deal with the flow of data in real time [2].
The successful implementation of this hybrid data compression system in our smart gateway not only reduces the space required for data storage, but also accelerates lossless data transfer over the network and to the disk. In addition, the system has a model for automatic and intelligent recognition and classification of data sources according to the data structure and the original format.
However, a use case of lossless data compression algorithms was applied to assess the performance of the hybrid system. In addition, a comparative study of metric parameters for data compression was carried out to highlight the advantages and limitations of this system. Our design demonstrates an advanced IoT data processing system for medical and health monitoring, based on an improved global approach to advanced data compression methods [3].
Keywords:
Internet of things, healthcare, data processing, data compression, Smart Gateway, Lossless algorithms.
References:
[1] https://experiences.microsoft.fr/business/intelligenceartificielle-ia-business/sante-connectee-chiffres/.
[2] Capteurs pour la télésurveillance médicale. Capteurs, algorithmes et réseaux IRBM, Volume 30, Issue 3, June 2009, Pages 93-103.
[3] Smart e-Health Gateway: Bringing Intelligence to Internetof-Things Based Ubiquitous Healthcare Systems DOI:10.1109/CCNC.2015.7158084 Conference: 12th Annual IEEE Consumer. Communications and Networking Conference (CCNC), At USA, Volume: 826-834.
[4] https://www.semanticscholar.org/paper/Lossless-Message-Compression-Bachelor-Thesis-in-Karlsson Hansson/6548c6f508296218e7edb28f0263e5a3e7db5769 .
[5] Secure and safety health care monitoring system based on IoT. SSRG International Journal of Computer Science and Engineering (SSRG – IJCSE) – Special Issue ICFTESH Mar 2019.
[6] Sensors Data Collection Architecture in the Internet of Mobile Things as a Service (IoMTaaS) Platform. DOI: 10.1109/I-SMAC.2017.8058245. Conference: IEEE International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud.
[7] Modern Lossless Compression Techniques: Review, Comparison and Analysis. Conference Paper · February 2017 DOI: 10.1109/ICECCT.2017.8117850.
[8] Hardware-accelerated Fast Lossless Compression Based on LZ4 Algorithm. ICDSP 2019: Proceedings of the 2019 3rd International Conference on Digital Signal Processing February 2019 Pages 65–68.
[9] Markus Oberhumer. LZO Data Compression Library http://www.oberhumer.com/opensource/lzo/.
[10] Julian Seward. A program and library for data compression. http://www.bzip.org.
[11] Yann Collet. Real Time Data Compression-LZ4 http://fastcompression.blogspot.se/p/lz4.html.
[12] TCIA Collections: https://www.cancerimagingarchive.net/
[13] Wearable IoT enabled real-time health monitoring system Jie Wan, Munassar A. A. H. Al-awlaqi, Ming Song Li, Michael O’Grady, Xiang GU, Jin Wang & Ning Cao EURASIP Journal on Wireless Communications and Networking volume 2018, Article number: 298 (2018).
[14] S.R. Kodituwakku et al. / Indian Journal of Computer Science and Engineering.
[15] A Survey of Image Compression Techniques in an Agriculture Field. SSRG International Journal of Computer Science and Engineering (SSRG – IJCSE) – Special Issue ICFTESH Feb 2019.
[16] CPTAC-CM: https://wiki.cancerimagingarchive.net/display/Public/CPTAC-CM and https://app.box.com/s/gplxy09gr8adu4ay31eaqqxikjd4mh3p/f
older/93339421102.
[17] IEEE Standard for Medical Device Communication, Overview and Framework. In ISO/IEEE 11073 Committee,1996.