Data Analytics on IoT-based Health Monitoring System
Mayank Murali1, Mahima Bhargava2, Snehaa G3, Anuj Anand4, Md Amaan Haque5, Vergin Raja Sarobin M6
1Mayank Murali, B. Tech Student, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India.
2Mahima Bhargava, B. Tech Student, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India.
3Snehaa G, B. Tech Student, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India.
4Anuj Anand, B. Tech Student, School of Electrical and Electronics Engineering, Vellore Institute of Technology, Chennai, India.
5Md Amaan Haque, B. Tech Student, School of Electrical and Electronics Engineering, Vellore Institute of Technology, Chennai, India.
6Vergin Raja Sarobin M, Assistant Professor, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India.
Manuscript received on 10 April 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 220-223 | Volume-8 Issue-1, May 2019 | Retrieval Number: A3033058119/19©BEIESP
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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: In recent times, health problems like cardiac failure, lung failures and heart related diseases are arising day by day at a very high rate. To address these problems, a sustained health monitoring becomes imperative. By regular health monitoring, diseases can be diagnosed and treated early. A new concept which is emerging is by monitoring the health of a patient wirelessly. In this paper, we report the use of a body temperature sensor and a heartbeat sensor for an IoT-based health monitoring system. The set up involved relaying of data from the sensors to an Arduino which was then sent to the cloud via an Ethernet module. The collected data were further processed by applying various algorithms and classification was done. We present the results obtained from the processing of the data using various algorithms – Naive Bayes, Random Forest Tree and SVM- and their comparison based on accuracy, precision and classification time.
Index Terms: Cloud Based Data Analytics, Health Monitoring, Internet of Things, Prediction and Classification.
Scope of the Article: Classification