Big-Data Based Real-Time Interactive Growth Management System in Wireless Communications
Obesity in children and adolescents has become a severe social issue worldwide. More than 85% of obesity in children and adolescents develops into adult obesity or leads to adult diseases like high blood pressure, artery hardening, and diabetes because of unbalanced growth and development. For this reason, a long-term and systematic care system needs to be developed using wireless communications technologies. Although many of the world’s governments have tried a variety of obesity-care policies, a poor care system remains in the children- and adolescent-healthcare areas. Therefore, this study proposes the big-data-based real-time interactive growth management (RIGM) system for the integrated growth and development of children and adolescents in the wireless communications environment. In the development of the RIGM, the activity, heart rate, steps, and other kinds of bio-data that can be received from a smart device are monitored; the growth and development status is analyzed comprehensively in the platform that receives the bio-data through wireless communications, and it is interactively checked by an application in real time. After the designed child and adolescent growth-management system was tested, the possibility of its use as a systematic growth-management system was confirmed.
KeywordsWireless communication Big-data Platform Child and youth Data mining
This research was supported by Incheon Business Information Technopark.
- 3.Musaiger, A. O., Al-Mannai, M., & Al-Marzog, Q. (2014). Overweight and obesity among children (10–13 years) in Bahrain: A comparison between Two International Standards. Pakistan Journal of Medical Sciences, 30(3), 497–500.Google Scholar
- 5.Stark, M. J., Niederhauser, V. P., Camacho, J. M., & Shirai, L. (2011). The prevalence of overweight and obesity in children at a health maintenance organization in Hawai’i. Hawai’i Medical Journal, 70(7), 27–31.Google Scholar
- 10.Amin, R. U., & Inayat, I. (2017). An empirical study on acceptance of secure healthcare service in Malaysia, Pakistan, and Saudi Arabia: a mobile cloud computing perspective. Annals of Wireless Communications, 72(5–6), 253–264.Google Scholar
- 17.ISO/IEEE, 11073-20601: health informatics-person health device communication, application profile optimized exchange protocol. http://www.iso.org. Accessed 2 Aug 2018.
- 20.Althenyan, Q., Yaseen, Q., Jararweh, Y., & Al-Ayyoub, M. (2016). Cloud support for large scale e-healthcare systems. Annals of Wireless Communications, 17(9–10), 503–515.Google Scholar
- 21.Celdrán, A. H., Pérez, M. G., García Clemente, F. J., & Pérez, G. M. (2017). Preserving patients’ privacy in health scenarios through a multicontext-aware system. Annals of Wireless Communications, 72(9–10), 577–587.Google Scholar
- 23.Sebbak, F., & Benhammadi, F. (2017). Majority-consensus fusion approach for elderly IoT-based healthcare applications. Annals of Wireless Communications, 72(3–4), 157–171.Google Scholar