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Feasibility of Complex Operations on Real Time Data Stream at On-Surface Body Sensor for Ubiquitous HealthCare
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 166 - Number 10 |
| Year of Publication: 2017 |
| Authors: Chetna Laroiya, Vijay Bhushan Aggarwal |
10.5120/ijca2017914134
|
Chetna Laroiya, Vijay Bhushan Aggarwal . Feasibility of Complex Operations on Real Time Data Stream at On-Surface Body Sensor for Ubiquitous HealthCare. International Journal of Computer Applications. 166, 10 ( May 2017), 36-41. DOI=10.5120/ijca2017914134
Abstract
Rapid growth in the field of wireless technology, body area network, personal area network and miniaturization in device has led to continuous health monitoring of moving patient which further can result into emergence of technology driven enhancement in contemporary healthcare practices. Can we have an Intelligent Applications in HealthCare (with knowledge base and inference engine) which can work on real time data stream initiating at sensor. For that we need to think of an application which can analyze sensed data stream, based on the past experience or rules specified as its knowledgebase to take decisions with in definite latency or delay. Can we think of an application which could record patient’s physiological condition and can automate the dosage induction based on the oddity arising in it? Memory size and energy at sensor provided by different vendors are two major obstacles in the design of such an application. Sensor depletes maximum energy in data transmission which could be reduced in terms of data size and number of communications. In this paper finds three gaps in initiation of such an application namely (i) projections for at sensor UDBMS architecture to upkeep ubiquitous computing, (ii) construction of the SQL code to analyse sensor data stream (based on joint conditional probability) (iii) simulation of above code to compare (CPU time, elapsed time, communication time, communication energy) its execution at sensor with one device at some hop distance. Simulation results have obtained under various length real time sensor data stream are consistent and lead to the deduction that complex operation can be and should be advanced AP or at UI based sensor through SQL queries.
References
- B. Yu, “Wireless Body Area Networks for HealthCare: A Feasibility Study,” University of Florida, Florida, 2009.
- G. V. Luis Javier, T. C. Alicia and B. ,. Cláudia Jacy, “Routing Protocols in Wireless Sensor Networks,” Sensors, 2009.
- O. Chris, M. Aleksandar, C. Sanders and J. Email, “System Architecture of a Wireless Body Area Sensor Network for Ubiquitous Health Monitoring,” Journal of Mobile Multimedia, pp. 306 - 326, 2006.
- A. E. S. A. H. Z. I. Anis Ismail, “A New System Architecture for Pervasive Computing,” International Journal of UbiComp (IJU), pp. 22-37, 2011.
- D.-E. S. S. A. N. K. N. M. Anastasios Zafeiropoulos, “DATA MANAGEMENT IN SENSOR NETWORKS USING Semantic Web Technologies,” Nova Science Publisher, 2011.
- J.-F. M. P. C. L. Jesús Rodríguez-Molina, “Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application,” Sensors, 2013.
- L. Chetna and A. Dr. V.B., “Intelligence based Outlier Disclosure for UDBMS at Sensor :Wireless Body Sensor Network,” American Journal of Engineering Research, pp. 213-220, 2016.
- H. Y. Simon Fong, “The Six Technical Gaps between Intelligent Applications and Real -Time Data Mining Critical Review”.
- P. F. Jose Cecilio, “Wireless Sensor Network: Conepts and Components,” in Wireless Sensors in Heterogeneous Networked Systems, Coimbra, Springer International Publishing, 2014.
- A. D. Nicolas Tsiftes, “A Database in Every Sensor,” SenSys’11, ACM, pp. 316-329, 2011.
- G. R. Douglas, “LittleD:A Relational Database Management System for Resource Constrained Computing Devices,” UNIVERSITY OF BRITISH COLUMBIA, pp. 1-38, 2014.
- M. Khan, “UCI Machine Learning Repository,” Aug 1993. [Online]. Available: https://archive.ics.uci.edu/ml/datasets/Diabetes.
- C. L. C. Komalvalli, “ Energy Efficient Protocol in Wireless Sensor Network: Reactive On-Demand Routing,” vol. 2, no. 1, 2010.
- C. L. C. Komalavalli, “Metadata Challenge for Query Processing over Heterogeneous Wireless Sensor Network,” vol. 3, no. 4, 2011.
- E. ZURICH, Switzerland, 2007.
- R. L. Graeme Douglas, “LittleD: a SQL database for sensor nodes and embedded applications,” SAC '14 Proceedings of the 29th Annual ACM Symposium on Applied Computing, pp. 827-832, 2014.
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