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primary topic: OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32
type: Thesis
type: Article
abstract: Falls among the elderly are a serious health issue, where current solutions are often hindered by the weaknesses of cloud-based detection systems, such as high latency, significant power consumption, and internet dependency. This research aims to optimize a fall detection system by developing and testing a hybrid architecture based on edge computing on an Artificial Intelligence of Things platform using the ESP32-S3 microcontroller. The research method is Research and Development (R&D), wherein this study builds a functional wearable prototype using an MPU6050 sensor and an ESP32-S3 microcontroller. It implements a hybrid detection algorithm, which combines a threshold-based method as an initial trigger and a Random Forest classifier for final validation, to run entirely locally on the device. The study trains the Random Forest model offline using the public SisFall dataset and tests it through a series of simulated fall scenarios and Activities of Daily Living (ADLs) in a controlled laboratory environment. The results show that this edge-based system achieves a fall detection success rate of 91.25% with a very low false positive rate of 2.5%. The end-to-end system response time, from the moment of the incident until the notification is received, averages 4.85 seconds, which demonstrates the superiority of the edge computing architecture in terms of speed and efficiency compared to cloud-based approaches. This system offers a more responsive, reliable, and power-efficient solution. Keywords: Fall Detection, Edge Computing, Artificial Intelligence of Things, ESP32 microcontroller, Random Forest.
date: 2025-08-25
status: published
author list: authors
type: EPrint
type: ThesisEPrint
is part of: repository
has document: OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
subject: QA Mathematics
subject: QA76 Computer software
subject: TK Electrical engineering. Electronics Nuclear engineering

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document
has file: S_TE_2107975_Title.pdf
has part: S_TE_2107975_Title.pdf

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document
has file: S_TE_2107975_Chapter1.pdf
has part: S_TE_2107975_Chapter1.pdf

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document
has file: S_TE_2107975_Chapter3.pdf
has part: S_TE_2107975_Chapter3.pdf

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document
has file: S_TE_2107975_Chapter5.pdf
has part: S_TE_2107975_Chapter5.pdf

OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32 (Text)
type: Document

Universitas Pendidikan Indonesia
type: Organization

KODEPRODI20201#Teknik_Elektro_S1, Universitas Pendidikan Indonesia
type: Organization

- Galuh Yudha Prastyo
type: Person
given name: -
family name: Galuh Yudha Prastyo

- Agus Heri Setya Budi
type: Person
given name: -
family name: Agus Heri Setya Budi

HTML Summary of #144322 OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32
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primary topic: OPTIMASI SISTEM DETEKSI JATUH UNTUK LANJUT USIA BERBASIS EDGE COMPUTING MENGGUNAKAN ALGORITMA HYBRID PADA PLATFORM ESP32

QA Mathematics
type: Concept

QA76 Computer software
type: Concept

TK Electrical engineering. Electronics Nuclear engineering
type: Concept