Context Awareness Technology Using Parallel Mining for Ambient Assisted Living System

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    In  this  paper,  context  awareness  is  a  promising  technology  that  provides  health care services and a niche  area of big data paradigm. The   drift  in  Knowledge  Discovery  from  Data  refers  to  a  set  of  activities  designed  to refine and  extract  new knowledge from complex  datasets.  The   proposed  model  facilitates  a  parallel  mining  of  frequent item sets for Ambient Assisted Living (AAL) System [a.k.a. Health  Care [System]  of  big  data that  reside   inside  a  cloud  environment.  We  extend  a  knowledge  discovery framework for  processing  and  classifying  the  abnormal  conditions of patients having fluctuations in Blood Pressure (BP) and Heart Rate(HR) and storing  this data  sets  called  Big data  into Cloud to access from  anywhere   when  needed.   This   accessed data is used to compare the new data with it, which helps to know the patients health condition.

     

     


  • Keywords


    AAL; Big data; Cloud computing; Context management system; Rule induction

  • References


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      [2]. A.K. Dey (2000), ‘Providing Architectural Support for Building Context-Aware Applications’,Ph.D. dissertation, Georgia Institute of Technology.

      [3]. Amazon web services https://aws.amazon.com

      [4]. George Suciu, AlexandruVulpe, RazvanCraciunescu and Cristina Butca, Victor Suciu (2015), ‘Big Data Fusion for eHealth and Ambient Assisted Living Cloud Applications’, IEEE International Black Sea Conference on Communications and Networking, pp.102-106.

      [5]. Mulvenna, M, Carswell, W, McCullagh, P, Augusto, J.C., Huiru Zhen, Jeffers, P., Haiying Wang and Martin, S(2011)., ‘Visualization of Data for Ambient Assisted Living Services’, in Communications Magazine, IEEE , Vol.49, No.1, pp.110-117.

      [6]. P. R. Norris (2006), “Toward new vital signs: Tools and Mmethods for Physiologic Data Capture, Analysis, and Decision Support in Critical Care,” Ph.D. Dissertation, Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.

      [7]. Suciu, G, Vulpe, A., Craciunescu, R., Butca, C and Suciu, V (2015) "Big data fusion for eHealth and Ambient Assisted Living Cloud Applications," IEEE International Black Sea Conference on Communications and Networkingpp.102-106, 18-21.

      [8]. Venkatesh, V.; Vaithyanathan, V.; Kumar, M.P.; Raj, P.(2012), ‘A Secure Ambient Assisted Living (AAL) Environment: An implementation view,’ International Conference onComputer Communication and Informatics (ICCCI), pp.10

      [9]. Vivek.J, Devasanthiya, C.Vigneshwari (2016), ‘An enhanced tourism recommendation system with relevancy feedback mechanism and ontological specifications’.


 

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Article ID: 15046
 
DOI: 10.14419/ijet.v7i2.19.15046




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