Bd ca m big data for context-aware monitoring - a personalized knowledge discovery framework for assisted healthcare

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  • Do Your Projects With Technology Experts

    Copyright 2015 LeMeniz Infotech. All rights reserved

    Page number 1

    LeMeniz Infotech

    36, 100 Feet Road, Natesan Nagar, Near Indira Gandhi Statue, Pondicherry-605 005. Call: 0413-4205444, +91 9566355386, 99625 88976. Web : www.lemenizinfotech.com / www.ieeemaster.com Mail : projects@lemenizinfotech.com

    BDCaM: Big Data for Context-aware Monitoring

    - A Personalized Knowledge Discovery

    Framework for Assisted Healthcare

    ABSTRACT:

    Context-aware monitoring is an emerging technology that provides real-time

    personalised health-care services and a rich area of big data application. In this paper, we

    propose a knowledge discovery-based approach that allows the context-aware system to

    adapt its behaviour in runtime by analysing large amounts of data generated in ambient

    assisted living (AAL) systems and stored in cloud repositories. The proposed BDCaM

    model facilitates analysis of big data inside a cloud environment. It first mines the trends

    and patterns in the data of an individual patient with associated probabilities and utilizes

    that knowledge to learn proper abnormal conditions. The outcomes of this learning method

    are then applied in context-aware ecision-making processes for the patient. A use case is

    implemented to illustrate the applicability of the framework that discovers the knowledge of

    classification to identify the true abnormal conditions of patients having variations in blood

    pressure (BP) and heart rate (HR). The evaluation shows a much

    INTRODUCTION

    AN ambient assisted living (AAL) system consists of heterogeneous sensors and devices

    which generate huge amounts of patient-specific unstructured raw data everyday. Due to

    diversity of sensors and devices, the captured data also have wide variations. A data

    element can be from a few bytes of numerical value (e.g. HR = 72 bpm) to several

    gigabytes of video stream. For example, if we assume a single AAL system generates 100

    kilobytes data every second on average then it will become 2.93 abytes in one year. If any

    system targets to support say, 5 million patients, then the data amount will be 14 exabytes

    per year. Even if a healthcare system targets to analyse only continuous ECG of cardiac

    patients in real-time inside the cloud environment, then it will produce around 7 PetaBytes

    http://www.lemenizinfotech.com/http://www.ieeemaster.com/

  • Do Your Projects With Technology Experts

    Copyright 2015 LeMeniz Infotech. All rights reserved

    Page number 2

    LeMeniz Infotech

    36, 100 Feet Road, Natesan Nagar, Near Indira Gandhi Statue, Pondicherry-605 005. Call: 0413-4205444, +91 9566355386, 99625 88976. Web : www.lemenizinfotech.com / www.ieeemaster.com Mail : projects@lemenizinfotech.com

    data everyday from 3.5 million patients. Including these dynamically generated continuous

    monitoring data there are also huge amounts of persistent data such as patient profile,

    medical records, disease histories and social contacts.

    EXISTING SYSTEM

    In Existing System an attribute value set Ai is converted to a numerical value. Some

    context attributes already have numeric values (e.g. HR, BP, room perature). Numerical

    annotations are used for contexts having nominal value (e.g. activity). The static or

    historical context that have boolean values (e.g. symptoms) are combined in a single

    binary string which results a decimal value (e.g. 001100 converted to 12). So, after such

    numerical conversion every Ai has the value set described in Definition 1.

    PROPOSED SYSTEM

    In Proposed System we developed BDCaM, an extended version of the

    CoCaMAAL model. This includes the functionalities of learning and the knowledge

    discovery process to find patient-specific anomalies using large amounts of data

    ADVANTAGE OF PROPOSED SYSTEM

    Faster learning with greater knowledge

    Reduce the transmission of repeated false alerts

    Innovative architectural model for context-aware monitoring

    Step learning methodology

    Demonstrate the performance and efficiency of BDCaM model

    http://www.lemenizinfotech.com/http://www.ieeemaster.com/

  • Do Your Projects With Technology Experts

    Copyright 2015 LeMeniz Infotech. All rights reserved

    Page number 3

    LeMeniz Infotech

    36, 100 Feet Road, Natesan Nagar, Near Indira Gandhi Statue, Pondicherry-605 005. Call: 0413-4205444, +91 9566355386, 99625 88976. Web : www.lemenizinfotech.com / www.ieeemaster.com Mail : projects@lemenizinfotech.com

    ARCHITECTURE:

    http://www.lemenizinfotech.com/http://www.ieeemaster.com/

  • Do Your Projects With Technology Experts

    Copyright 2015 LeMeniz Infotech. All rights reserved

    Page number 4

    LeMeniz Infotech

    36, 100 Feet Road, Natesan Nagar, Near Indira Gandhi Statue, Pondicherry-605 005. Call: 0413-4205444, +91 9566355386, 99625 88976. Web : www.lemenizinfotech.com / www.ieeemaster.com Mail : projects@lemenizinfotech.com

    HARDWARE REQUIREMENTS:

    System : Pentium IV 2.4 GHz.

    Hard Disk : 40 GB.

    Floppy Drive : 44 Mb.

    Monitor : 15 VGA Colour.

    SOFTWARE REQUIREMENTS:

    Operating system : Windows 7.

    Coding Language : Java 1.7 ,Hadoop 0.8.1

    Database : MySql 5

    IDE : Eclipse

    http://www.lemenizinfotech.com/http://www.ieeemaster.com/

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