Data Organization and Knowledge Inference from Sensor Database for Smart Wear

Authors(3) :-Dr. Nilamadhab Mishra, Kindie Alebachew, Bikash Chandra Patnaik

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 patientís 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.

Authors and Affiliations

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

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

  1. Mishra, N., Lin, C. C., & Chang, H. T. (2014). Cognitive inference device for activity supervision in the elderly. The Scientific World Journal, 2014.
  2. Suryadevara, N. K., & Mukhopadhyay, S. C. (2012). Wireless sensor network based home monitoring system for wellness determination of elderly. Sensors Journal, IEEE, 12(6), 1965-1972.
  3. Suryadevara, N. K., Gaddam, A., Mukhopadhyay, S. C., & Rayudu, R. K. (2011, November). Wellness determination of inhabitant based on daily activity behaviour in real-time monitoring using Sensor Networks. In Sensing Technology (ICST), 2011 Fifth International Conference on (pp. 474-481). IEEE.
  4. Mishra, N., Lin, C. C., & Chang, H. T. (2015). A cognitive adopted framework for IoT big-data management and knowledge discovery prospective. International Journal of Distributed Sensor Networks, 11(10), 718390.
  5. Mishra, N., Lin, C. C., & Chang, H. T. (2014, December). A cognitive oriented framework for IoT big-data management prospective. In Communication Problem-Solving (ICCP), 2014 IEEE International Conference on (pp. 124-127). IEEE.
  6. Chang, H. T., Mishra, N., & Lin, C. C. (2015). IoT Big-Data Centred Knowledge Granule Analytic and Cluster System for BI Applications: A Case Base Analysis. PloS one, 10(11), e0141980.
  7. Mishra, N., Chang, H. T., & Lin, C. C. (2014). Data-centric knowledge discovery strategy for a safety-critical sensor application. International Journal of Antennas and Propagation, 2014.
  8. Mishra, N., Chang, H. T., & Lin, C. C. (2015). An Iot knowledge reengineering framework for semantic knowledge analytics for BI-services. Mathematical Problems in Engineering, 2015.
  9. Mishra, N. (2011). A Framework for associated pattern mining over Microarray database. International Journal of Global Research in Computer Science (UGC Approved Journal), 2(2).
  10. Mishra, N., Chang, H. T., & Lin, C. C. (2018). Sensor data distribution and knowledge inference framework for a cognitive-based distributed storage sink environment. International Journal of Sensor Networks, 26(1), 26-42.
  11. Mishra N, (2017). "In-network Distributed Analytics on Data-centric IoT Network for BI-service Applications", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN: 2456-3307, Volume 2, Issue 5, pp.547-552, September-October.2017.
  12. Patnaik, B. C., & Mishra, N. (2016). A Review on Enhancing the Journaling File System. Imperial Journal of Interdisciplinary Research, 2(11).
  13. Chang, H. T., Li, Y. W., & Mishra, N. (2016). mCAF: a multi-dimensional clustering algorithm for friends of social network services. SpringerPlus, 5(1), 757.
  14. Chang, H. T., Liu, S. W., & Mishra, N. (2015). A tracking and summarization system for online Chinese news topics. Aslib Journal of Information Management, 67(6), 687-699.

Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1039-1044
Manuscript Number : CSEIT1831209
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Dr. Nilamadhab Mishra, Kindie Alebachew, Bikash Chandra Patnaik , "Data Organization and Knowledge Inference from Sensor Database for Smart Wear", International 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.
Journal URL : http://ijsrcseit.com/CSEIT1831209

Article Preview