An Implementation of Genetic Algorithms in Big Data Processing for Medical Data
G. Renukadevi1, K Selvakumar2, S. Tamilarasan3, S. Venkatakrishnan4
1G. Renukadevi*, Research Scholar, Department of Computer Science & Engineering, Annamalai University, TN, India.
2Dr. K. Selvakumar, Department of Information Technology, Annamalai University, TN, India.
3S. Tamilarasan, Department of Computer Science, Bharathiar University, TN, India.
4Dr. S. Venkatakrishnan, Department of Computer Science, Annamalai University, TN, India
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 2215-2217 | Volume-9 Issue-3, February 2020. | Retrieval Number: C4852029320/2020©BEIESP | DOI: 10.35940/ijeat.C4852.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The large amount of real time medical measurement parameters stored in the SQL server needs processing using a specific algorithm. One of the big data processing techniques is available for medical data is Genetic algorithm. The acquired medical parameters are combined together to predict or diagnose the disease using the genetic algorithm. In this paper, the genetic algorithm is used to process the medical measurements data. The medical parameters are posted temporarily in the Representational Structure (REST) Application Program Interface (API) using a gateway protocol MQTT. The genetic algorithm can easily diagnose the disease using the existing stored parameters. The medical parameters of the patient like ECG, Blood pressure and skin temperature are posted frequently in the cloud server for continuous monitoring, and the huge data is also processed using this proposed method.
Keywords: Big data Processing, Genetic Algorithm, Medical data, REST API, SQL Server, Thermistor, Digital Sphygmomanometer, Node MCU, HTTP Gateway