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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM17283

IoT BASED WHEELCHAIR FALL DETECTION SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM17283

Volume:

7 |

1 |

Jan 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KA

K. Amogha

CS

C. Sahithi

IH

I. Harish

DYS

Dr. Y. Srinivasulu

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Abstract

It is important to take care of our elderly people and keep an eye on their well-being and security. It is likely that they have a high risk of falling because of their fragile bones and joints, which brings in the usage of wheelchair for most of the old people. A wheelchair-bound individual who is physically impaired needs to be watched out for falls as well. There are currently monitoring systems using CCTV cameras, but they are very expensive. The average person cannot afford such a system. As a result, we suggest an affordable fall detection system using the newest technology such as Internet of Things (IoT). The system uses gyroscope and accelerometer sensors to detect individual movements. Both collaborate to detect the fall events improving the detection’s accuracy. It might be mounted on a person’s hand or wheelchair for finding. The sensor is connected to a microcontroller so that it can continuously monitor the data about the increasing speed. What if the individual did not fall and the warning given was false? The framework allows the alarm to be turned off if the individual presses the snooze button within 5 seconds. Therefore, IoT will reduce user effort while also generating fertile work that makes accessing the system simple.

KEYWORDS

Arduino UNO R3 w h e e l c h a i r f a l l d e t e c t i o n a c c u r a c y S e n s o r s

Cite This Article

K. Amogha, C. Sahithi, I. Harish, Dr. Y. Srinivasulu, "IoT BASED WHEELCHAIR FALL DETECTION SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 1, Jan 2023. https://doi.org/10.55041/IJSREM17283

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Publication Date

1/31/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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22

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5

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The authors declare no conflict of interest related to this research work.

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