A Comprehensive and Modern Framework for Cloud-based Mobile Maternity Data Management
Özet
The pregnancy period holds great significance in a woman's life, and maternity healthcare plays a crucial role in society's overall healthcare system. However, there are various issues and limitations associated with existing services aimed at supporting pregnant women. Firstly, there is a lack of an electronic system for sharing maternity data between hospitals and clinics. The current systems do not effectively utilize web and mobile technology, and there is a lack of a comprehensive and widespread system. Most health clinics still rely on traditional approaches. Secondly, approximately 20% of pregnant women require hospitalization for varying durations due to complications such as bleeding or low placenta. Unfortunately, there is no monitoring service available at home to minimize the number of hospitalized pregnant women. Additionally, rural pregnant women, who tend to have higher poverty rates and poorer health, face additional difficulties due to limited access to doctors, hospitals, and healthcare resources. Currently, there is no monitoring system specifically designed for rural pregnant women. Utilizing mobile devices for monitoring pregnant women provides a potential solution to these problems. Mobile maternity monitoring offers an opportunity to share maternity data and monitor pregnant women at home, reducing the need for hospitalization. However, maternity monitoring through mobile devices may also give rise to other technical challenges. The first challenge pertains to the quality, availability, accessibility, security, and privacy of patients' data. The second challenge involves the limitations of mobile devices, including memory, battery life, and processor speed. This study addresses these problems through a comprehensive literature review on maternity data management, pervasive mobile healthcare systems, cloud computing, and mobile healthcare systems on cloud computing. Subsequently, a new architecture is proposed to tackle these challenges.
Referanslar
Z. Gou, S. Yamaguchi, and B. Gupta, "Analysis of various security issues and challenges in cloud computing environment: a survey," Identity Theft: Breakthroughs in Research and Practice, pp. 221-247, 2017.
M. Andoni et al., "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and sustainable energy reviews, vol. 100, pp. 143-174, 2019.
S. Gupta, P. Kumar, and A. Abraham, "A profile based network intrusion detection and prevention system for securing cloud environment," International Journal of Distributed Sensor Networks, vol. 9, no. 3, p. 364575, 2013.
U. Habiba, R. Masood, M. A. Shibli, and M. A. Niazi, "Cloud identity management security issues & solutions: a taxonomy," Complex Adaptive Systems Modeling, vol. 2, pp. 1-37, 2014.
S. Iqbal et al., "On cloud security attacks: A taxonomy and intrusion detection and prevention as a service," Journal of Network and Computer Applications, vol. 74, pp. 98-120, 2016.
I. M. Khalil, A. Khreishah, and M. Azeem, "Cloud computing security: A survey," Computers, vol. 3, no. 1, pp. 1-35, 2014.
H. Ahani and V. Izadi, "Detection of Different Bearing Faults in a Permanent Magnet Synchronous Motor using PWT and LVQNN," in 2020 XI National Conference with International Participation (ELECTRONICA), 2020: IEEE, pp. 1-4.
V. Izadi, M. Abedi, and H. Bolandi, "Supervisory algorithm based on reaction wheel modelling and spectrum analysis for detection and classification of electromechanical faults," IET Science, Measurement & Technology, vol. 11, no. 8, pp. 1085-1093, 2017.
S. Mugunthan, "Soft computing based autonomous low rate DDOS attack detection and security for cloud computing," J. Soft Comput. Paradig.(JSCP), vol. 1, no. 02, pp. 80-90, 2019.
S. Namasudra, "Cloud computing: A new era," Journal of Fundamental and Applied Sciences, vol. 10, no. 2, 2018.
S. Namasudra, P. Roy, and B. Balusamy, "Cloud computing: fundamentals and research issues," in 2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM), 2017: IEEE, pp. 7-12.
A. Yousefiankalareh, A. Najari, and M. Hosseynzadeh, "Tree-based Routing Protocol in Wireless Sensor Networks using Optimization Algorithm Batch Particles with a Mobile Sink," in 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET), 2020: IEEE, pp. 1-5.
A. Shameli-Sendi, M. Pourzandi, M. Fekih-Ahmed, and M. Cheriet, "Taxonomy of distributed denial of service mitigation approaches for cloud computing," Journal of Network and Computer Applications, vol. 58, pp. 165-179, 2015.
S. Tweneboah-Koduah, B. Endicott-Popovsky, and A. Tsetse, "Barriers to government cloud adoption," International Journal of Managing Information Technology, vol. 6, no. 3, pp. 1-16, 2014.
P. You, Y. Peng, W. Liu, and S. Xue, "Security issues and solutions in cloud computing," in 2012 32nd International Conference on Distributed Computing Systems Workshops, 2012: IEEE, pp. 573-577.
S. Yu, Y. Tian, S. Guo, and D. O. Wu, "Can we beat DDoS attacks in clouds?," IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 9, pp. 2245-2254, 2013.
Doukas, C., Pliakas, T., & Maglogiannis, I. (2010). Mobile healthcare information management utilizing Cloud Computing and Android OS. Paper presented at the Conf Proc IEEE Eng Med Biol Soc.
Kay, M. (2011). mHealth: New horizons for health through mobile technologies. World Health Organization, 66-71.
Keller, E., & Rexford, J. (2010). The “Platform as a service” model for networking. INM/WREN, 1-6.
Lupse, O. S., Vida, M. M., & Stoicu-Tivadar, L. (2012). Cloud Computing and Interoperability in Healthcare Information Systems. Paper presented at the INTELLI 2012, The First International Conference on Intelligent Systems and Applications, 81-85.
G. Gavrilov and V. Trajkovik, "Security and privacy issues and requirements for healthcare cloud computing," ICT Innovations, pp. 143-152, 2012.
Y. Karaca, M. Moonis, Y.-D. Zhang, and C. Gezgez, "Mobile cloud computing based stroke healthcare system," International Journal of Information Management, vol. 45, pp. 250-261, 2019.
C. Lubamba and A. Bagula, "Cyber-healthcare cloud computing interoperability using the HL7-CDA standard," in 2017 IEEE Symposium on Computers and Communications (ISCC), 2017: IEEE, pp. 105-110.
E. Mehraeen, M. Ghazisaeedi, J. Farzi, and S. Mirshekari, "Security challenges in healthcare cloud computing: a systematic review," Global journal of health science, vol. 9, no. 3, p. 157, 2016.
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