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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | HUMAN ACTIVITY RECOGNITION WITH SMARTPHONES USING MACHINE LEARNING PROCESS |
| Authors Name: | Chava Lohith , GAJULA PAVAN KALYAN , Dr.S.PRINCE MARY |
| Unique Id: | IJSDR2304100 |
| Published In: | Volume 8 Issue 4, April-2023 |
| Abstract: | To make human exercises straightforward, human exercises should be anticipated in view of data produced by the sensor Over the most recent couple of years, it has drawn in a great deal of consideration on account of various exercises utilizing current PC hardware It is notable to order data about exercises like walking and stair climbing Slippery steps, sitting, and standing were created with the aid of a speedometer and a spinner, and the sensor signal (from the speedometer and whirligig) was initially handled by a commotion channel. The high velocity movement sensor which is touchy to development was one of a kind in that it utilized a Butterworth under a body speedometer and a speed channel. Incredible power is viewed as just a little part the course of the item gotten by computing the occasional change The objective is to choose Al methods for human exercises. Data set Analysis and Machine Learning Techniques (SMLT) innovation is tied in with getting such data, adjusting information single-variable investigation, twofold factor examination and different things esteem examination information examination information handling/information readiness, and imaging on the informational index Recommend a machine to figure out how to accurately foresee the worth of a stock Esteem given by expanding the offer cost or the cost of government contrasted with an Al calculation Mercever the Department of Transportation and Evaluation analyzes and examines the presentation of different Al calculations. Data progressive system grids, informational collections, and stage appraisal reports are quickly discovered, and the results demonstrate that the presentation of the suggested Al calculation can hold up to accuracy, memory, and F1 scores. |
| Keywords: | Keywords – Human Activity Recognition,Machine Learning,Decision tree,Random forest,SVM |
| Cite Article: | "HUMAN ACTIVITY RECOGNITION WITH SMARTPHONES USING MACHINE LEARNING PROCESS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.540 - 543, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304100.pdf |
| Downloads: | 000337071 |
| Publication Details: | Published Paper ID: IJSDR2304100 Registration ID:205138 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: 540 - 543 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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