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

Dwi Rangga Okta Zuhdiyanto; Yuli Asriningtias

doi:10.29207/resti.v9i1.6105

Dwi Rangga Okta Zuhdiyanto Universitas Teknologi Yogyakarta
Yuli Asriningtias Universitas Teknologi Yogyakarta

DOI: https://doi.org/10.29207/resti.v9i1.6105

Keywords: dementia, Global Positioning System (GPS), Internet of Things (IoT), real-time monitoring, reminder application

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.

Downloads

Download data is not yet available.

References

N. Aljojo et al., “Alzheimer assistant: a mobile application using Machine Learning,” Revista Română de Informatică și Automatică, vol. 30, no. 4, pp. 7–26, Dec. 2020, doi: 10.33436/v30i4y202001.

S. Deepa, L. Dhanesh, V. Danusha, K. Divya Dath, G. K. Pavadhaarini, and C. Shobana Sri, “Dementia People Tracking System,” Advances in Parallel Computing, vol. 39, pp. 744–748, 2021, doi: 10.3233/APC210273.

R. Reena, R. Srishti, M. Harini, A. Mohamed, E. Surayyo, and R. S. Kumar, “IoT-Based Assistant for Alzheimer’s Patient with Reminder System and Tracking Using GPS,” in E3S Web of Conferences, EDP Sciences, Jul. 2023. doi: 10.1051/e3sconf/202339904053.

“Innovative solutions for dementia care using ICT: A qualitative content analysis,” 2020.

F. S. Abi and Y. Asriningtias, “Model Sistem Keamanan Pintu Rumah Berbasis Internet Of Things House Door Security System Model Based On The Internet Of Things,” Journal of Information Technology and Computer Science (INTECOMS), vol. 6, no. 2, 2023.

Proceedings of the International Conference on Intelligent Computing and Control Systems (ICICCS 2020) : 13-15 May, 2020. IEEE, 2020.

M. V Klymenko and A. M. Striuk, “Development of software and hardware complex of GPS-tracking,” 2020. [Online]. Available: http://mpz.knu.edu.ua/pro-kafedru/vikladachi/224-andrii-striuk

R. Mallik, D. Sing, and R. Bandyopadhyay, “GPS Tracking App for Police to Track Ambulances Carrying COVID-19 Patients for Ensuring Safe Distancing,” Transactions of the Indian National Academy of Engineering, vol. 5, no. 2, pp. 181–185, Jun. 2020, doi: 10.1007/s41403-020-00116-8.

J. G. V. Etibou and S. Pierre, “IoT Devices Modular Security Approach Using Positioning Security Engine,” IEEE Access, pp. 1–1, Jul. 2024, doi: 10.1109/access.2024.3424658.

M. Désormeaux-Moreau et al., “Mobile apps to support family caregivers of people with Alzheimer disease and related dementias in managing disruptive behaviors: Qualitative study with users embedded in a scoping review,” JMIR Aging, vol. 4, no. 2, Apr. 2021, doi: 10.2196/21808.

G. R. Chelberg, M. Neuhaus, A. Mothershaw, R. Mahoney, and L. J. Caffery, “Mobile apps for dementia awareness, support, and prevention–review and evaluation,” Disabil Rehabil, vol. 44, no. 17, pp. 4909–4920, 2022, doi: 10.1080/09638288.2021.1914755.

K. Hackett et al., “Remind Me To Remember: A pilot study of a novel smartphone reminder application for older adults with dementia and mild cognitive impairment,” Neuropsychol Rehabil, pp. 1–29, 2020, doi: 10.1080/09602011.2020.1794909.

A. Sheikhtaheri and F. Sabermahani, “Applications and Outcomes of Internet of Things for Patients with Alzheimer’s Disease/Dementia: A Scoping Review,” 2022, Hindawi Limited. doi: 10.1155/2022/6274185.

J. Howes, Y. Denier, and C. Gastmans, “Electronic Tracking Devices for People With Dementia: Content Analysis of Company Websites,” JMIR Aging, vol. 5, no. 4, Oct. 2022, doi: 10.2196/38865.

M. Doyle, E. S. Nwofe, C. Rooke, K. Seelam, J. Porter, and D. Bishop, “Implementing global positioning system trackers for people with dementia who are at risk of wandering,” Dementia, vol. 23, no. 6, pp. 964–980, Aug. 2024, doi: 10.1177/14713012241248556.

A. Cullen, M. K. A. Mazhar, M. D. Smith, F. E. Lithander, M. Breasail, and E. J. Henderson, “Wearable and Portable GPS Solutions for Monitoring Mobility in Dementia: A Systematic Review,” Sensors, vol. 22, no. 9, May 2022, doi: 10.3390/s22093336.

J. B. Madavarapu et al., “Hot Watch: IOT based :Wearable Health Monitoring System,” IEEE Sens J, 2024, doi: 10.1109/JSEN.2024.3424348.

A. Gallo et al., “The SI4CARE project: using wearable devices for assisting people with dementia in Calabria,” 2023, doi: 10.20944/preprints202301.0427.v1.

K. I°leri, A. Duru, and I. R. Karas, “Development Of Iot Enabled Global Tracking System And Mobile Application For People With Alzheimer’s Disease,” in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, International Society for Photogrammetry and Remote Sensing, Dec. 2021, pp. 287–290. doi: 10.5194/isprs-Archives-XLVI-4-W5-2021-287-2021.

A. Rane, A. Nayak, R. Kamble, S. Panchal, and M. Palinje, “Health Monitoring/Security System for Alzheimer Patient,” International Research Journal of Engineering and Technology, 2020, [Online]. Available: www.irjet.net

M. Nosike Chinwike, E. Ifiok, and E. Edet Ekott, “Development Of Microcontroller-Based Tricycle Tracking Using Gps And Gsm Modules,” 2020. [Online]. Available: www.jmest.org

H. E. Adardour, M. Hadjila, S. M. H. Irid, T. Baouch, and S. E. Belkhiter, “Outdoor Alzheimer’s Patients Tracking Using an IoT System and a Kalman Filter Estimator,” Wirel Pers Commun, vol. 116, no. 1, pp. 249–265, Jan. 2021, doi: 10.1007/s11277-020-07713-4.