Real-Time Location Monitoring and Routine Reminders Based on Internet of Things Integrated with Mobile for Dementia Disorder

The increasing number of dementia sufferers worldwide demands a new approach to monitoring daily activities and locations to reduce the risk of getting lost. This study develops a real-time location monitoring and routine reminder system based on the Internet of Things (IoT), integrated with a mobile application. The system is designed to assist individuals with dementia, particularly elderly and younger adults with cognitive impairments, in performing daily routines independently, while providing a sense of security for families and caregivers through real-time location tracking features. This technology utilizes GPS for accurate location monitoring, daily activity reminders, and automatic notifications for caregivers in case of deviations from usual routes. The system development includes prototype creation that consisting of a mobile application and IoT tools such as the ESP32 WROOM microcontroller, Ublox Neo6M V2 GPS module, and SIM800L V2 GSM module. Functionality testing and impact evaluation were conducted to assess its effectiveness in improving the quality of life for dementia sufferers and facilitating monitoring for caregivers. With features such as daily reminders, emergency contacts, and real-time data integration, this system is intended not only for dementia patients but also for families and caregivers seeking tools to ensure the safety and comfort of the sufferers. It is expected that this research will enhance the independence of dementia patients in performing daily activities and provide innovative solutions through IoT technology to improve well-being across different age groups.

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Publication Details

Journal
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Published
2025-01-26
DOI
https://doi.org/10.29207/resti.v9i1.6105
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.84
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article

Real-Time Location Monitoring and Routine Reminders Based on Internet of Things Integrated with Mobile for Dementia Disorder

Yuli Asriningtias, Dwi Rangga Okta Zuhdiyanto
1 citations
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Brain Tumor Detection and Classification
0.84
article

Real-Time Location Monitoring and Routine Reminders Based on Internet of Things Integrated with Mobile for Dementia Disorder

Yuli Asriningtias, Dwi Rangga Okta Zuhdiyanto
article en
1 citations

Abstract

The increasing number of dementia sufferers worldwide demands a new approach to monitoring daily activities and locations to reduce the risk of getting lost. This study develops a real-time location monitoring and routine reminder system based on the Internet of Things (IoT), integrated with a mobile application. The system is designed to assist individuals with dementia, particularly elderly and younger adults with cognitive impairments, in performing daily routines independently, while providing a sense of security for families and caregivers through real-time location tracking features. This technology utilizes GPS for accurate location monitoring, daily activity reminders, and automatic notifications for caregivers in case of deviations from usual routes. The system development includes prototype creation that consisting of a mobile application and IoT tools such as the ESP32 WROOM microcontroller, Ublox Neo6M V2 GPS module, and SIM800L V2 GSM module. Functionality testing and impact evaluation were conducted to assess its effectiveness in improving the quality of life for dementia sufferers and facilitating monitoring for caregivers. With features such as daily reminders, emergency contacts, and real-time data integration, this system is intended not only for dementia patients but also for families and caregivers seeking tools to ensure the safety and comfort of the sufferers. It is expected that this research will enhance the independence of dementia patients in performing daily activities and provide innovative solutions through IoT technology to improve well-being across different age groups.

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)Vol. 9(1)
Universitas Teknologi Yogyakarta (ID)
Openalex Percentile: Top 29%
Brain Tumor Detection and Classification
0.84
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