relation: https://eprints.untirta.ac.id/42338/
title: SISTEM PENDETEKSI JATUH PADA MANUSIA MENGGUNAKAN SENSOR ACCELEROMETER
creator: Aprilliana, Fhery
subject: T Technology (General)
subject: TK Electrical engineering. Electronics Nuclear engineering
description: A fall is defined as an incident where a subject moves from a standing position and then immediately lies down or sits on the ground or floor with or without awareness. Falling is something that often happens to elderly people when doing activities. The risk of falling in older people is higher than in younger people. The impact of a fall can cause fatal injuries to elderly people. The Internet of Things (IoT) is a concept where objects can communicate over a network, enabling data transfer without the need for direct interaction between humans or between humans and devices such as computers. It is necessary to supervise the elderly with a high risk of falling by using a fall detection device. Based on tests conducted by conducting 40 fall tests, 39 falls were successfully identified and 1 failed to be identified. Testing 50 times of daily activities was successfully identified as a non-falling condition. The buzzer test was successfully activated instantly and the Telegram notification was 100% successfully sent.
date: 2024-06-14
type: Thesis
type: NonPeerReviewed
format: text
language: en
identifier: https://eprints.untirta.ac.id/42338/10/Fhery%20Aprilliana_3332170099_Full%20Text.pdf
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identifier: https://eprints.untirta.ac.id/42338/11/Fhery%20Aprilliana_3332170099_01.pdf
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identifier: https://eprints.untirta.ac.id/42338/3/Fhery%20Aprilliana_3332170099_02.pdf
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identifier: https://eprints.untirta.ac.id/42338/5/Fhery%20Aprilliana_3332170099_04.pdf
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identifier: https://eprints.untirta.ac.id/42338/6/Fhery%20Aprilliana_3332170099_05.pdf
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identifier: https://eprints.untirta.ac.id/42338/7/Fhery%20Aprilliana_3332170099_CP.pdf
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identifier: https://eprints.untirta.ac.id/42338/8/Fhery%20Aprilliana_3332170099_lamp.pdf
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identifier: https://eprints.untirta.ac.id/42338/9/Fhery%20Aprilliana_3332170099_ref.pdf
identifier:   Aprilliana, Fhery  (2024) SISTEM PENDETEKSI JATUH PADA MANUSIA MENGGUNAKAN SENSOR ACCELEROMETER.  S1 thesis, Fakultas Teknik Universitas Sultan Ageng Tirtayasa.