Edge Computing and Quantum Computing to Find Statistics of Pandemic

Authors

  • Takudzwa Fadziso Chinhoyi University of Technology

DOI:

https://doi.org/10.18034/ei.v6i2.553

Keywords:

Quantum Edge, Pandemics Disease, Healthcare Statistics, Qubits, Bits

Abstract

Edge computing and quantum computing to find statistics of pandemic’ analysis the use of edge and quantum computing in tracking the events happening in the world to get the statistical analysis done to find pandemic causing factors and situations so that authorities can be notified so that a potential pandemic can be avoided in the near future. An edge computing system enables customer data to be processed at the edge of the network to as close as possible to the originating source. Quantum computing is an aspect of computer processing that concentrates on creating machines, computer systems, and technology using the tenets of quantum theory. The application of edge and quantum computing in the healthcare sector, just like in other industries, can enable significant advantages that only traditional computers may not bring.

Downloads

Download data is not yet available.

Author Biography

Takudzwa Fadziso, Chinhoyi University of Technology

Institute of Lifelong Learning and Development Studies, Chinhoyi University of Technology, ZIMBABWE

References

Ganapathy, A. (2015). AI Fitness Checks, Maintenance and Monitoring on Systems Managing Content & Data: A Study on CMS World. Malaysian Journal of Medical and Biological Research, 2(2), 113-118. https://doi.org/10.18034/mjmbr.v2i2.553

Ganapathy, A. (2016a). Blockchain Technology Use on Transactions of Crypto Currency with Machinery & Electronic Goods. American Journal of Trade and Policy, 3(3), 115-120. https://doi.org/10.18034/ajtp.v3i3.552

Ganapathy, A. (2016b). Speech Emotion Recognition Using Deep Learning Techniques. ABC Journal of Advanced Research, 5(2), 113-122. https://doi.org/10.18034/abcjar.v5i2.550

Ganapathy, A. (2017). Friendly URLs in the CMS and Power of Global Ranking with Crawlers with Added Security. Engineering International, 5(2), 87-96. https://doi.org/10.18034/ei.v5i2.541

Ganapathy, A., & Neogy, T. K. (2017). Artificial Intelligence Price Emulator: A Study on Cryptocurrency. Global Disclosure of Economics and Business, 6(2), 115-122. https://doi.org/10.18034/gdeb.v6i2.558

Neogy, T. K., & Paruchuri, H. (2014). Machine Learning as a New Search Engine Interface: An Overview. Engineering International, 2(2), 103-112. https://doi.org/10.18034/ei.v2i2.539

Paruchuri, H. (2015). Application of Artificial Neural Network to ANPR: An Overview. ABC Journal of Advanced Research, 4(2), 143-152. https://doi.org/10.18034/abcjar.v4i2.549

Paruchuri, H. (2017). Credit Card Fraud Detection using Machine Learning: A Systematic Literature Review. ABC Journal of Advanced Research, 6(2), 113-120. https://doi.org/10.18034/abcjar.v6i2.547

Vadlamudi, S. (2015). Enabling Trustworthiness in Artificial Intelligence - A Detailed Discussion. Engineering International, 3(2), 105-114. https://doi.org/10.18034/ei.v3i2.519

Vadlamudi, S. (2016). What Impact does Internet of Things have on Project Management in Project based Firms?. Asian Business Review, 6(3), 179-186. https://doi.org/10.18034/abr.v6i3.520

Vadlamudi, S. (2017). Stock Market Prediction using Machine Learning: A Systematic Literature Review. American Journal of Trade and Policy, 4(3), 123-128. https://doi.org/10.18034/ajtp.v4i3.521

--0--

Downloads

Published

2018-12-21

How to Cite

Fadziso, T. (2018). Edge Computing and Quantum Computing to Find Statistics of Pandemic. Engineering International, 6(2), 143–154. https://doi.org/10.18034/ei.v6i2.553

Issue

Section

Peer Reviewed Articles