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  Published Paper Details:

  Paper Title

HUMAN ACTIVITY RECOGNITION WITH SMART PHONE DATASET

  Authors

  C .N.Sujatha,  Hari Alekhya,  Akhila chakrala,  S.Pooja Rao

  Keywords

Human activities recognition, intelligent system, accelerometer, train data , text data.

  Abstract


Human action acknowledgment is confirmation to screen the human development and exercises by anticipating improvements. It is an inconvenient issue, as immense number of acknowledgments are made each second, the passing idea of the acumen, and the nonappearance of a reasonable technique to relate accelerometer information to know the turns of events. In this paper, an insightful human movement framework acknowledgment is created. . The information present here is observed from 30 volunteers old enough going from 19 to 48 years. Every individual was told to follow a convention of exercises ((WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) while at the same time wearing a midriff mounted samsung system SII advanced cell. Using its embedded accelerometer and gyrator, we got 3-linearaly increasing speed up and 3-center point angular speed at a steady pace of 50Hz. The dataset determined has been subjectively allocated two individual sets, in which 70% of the volunteers was picked for making the readiness data and 30% the test data. This gives precision of about 96% for the substance data made out of 2947 models.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2005099

  Paper ID - 194234

  Page Number(s) - 727-731

  Pubished in - Volume 8 | Issue 5 | May 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  C .N.Sujatha,  Hari Alekhya,  Akhila chakrala,  S.Pooja Rao,   "HUMAN ACTIVITY RECOGNITION WITH SMART PHONE DATASET", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 5, pp.727-731, May 2020, Available at :http://www.ijcrt.org/papers/IJCRT2005099.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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