Data Organization and Knowledge Inference from Sensor Database for Smart Wear

Authors

  • Dr. Nilamadhab Mishra  Post Graduate Teaching & Research Department, School of Computing, Debre Berhan University, Debre Berhan, Ethiopia
  • Kindie Alebachew  School of Computing, Debre Berhan University, Debre Berhan, Ethiopia
  • Bikash Chandra Patnaik   Gandhi Institute of Engineering and Technology, Orissa, India

Keywords:

sensor database, smart wear, knowledge inference, physiological data, thing to people

Abstract

Sensor data base has found increasing applications in health care domain. A wide variety of Intensive Care Unit (ICU) applications use sensors such as ECG, EEG, blood pressure monitors, respiratory monitors, and a wide variety of other sensors from where huge amount of physiological signals/data are generated. The main research challenge is how to manage and organize those physiological data with an intention of tracking the condition of patient and providing time critical service information to the patient’s smartphone for emergency precautions. The volume and velocity of such data tends to big-data complications and the knowledge inferences from such data need to be performed in a time-critical fashion. In this paper, we discuss the physiological data organization approaches in order to provide the storage for large scale physiological data and the emerging Knowledge inference mechanism for transforming the physiological data into insights in the context of health-care application.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-02-28

Issue

Volume 3, Issue 1, January-February-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. Nilamadhab Mishra, Kindie Alebachew, Bikash Chandra Patnaik , " Data Organization and Knowledge Inference from Sensor Database for Smart Wear, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.1039-1044, January-February-2018.