Smart Home for Supporting Elderly Based On Ultrawideband Positioning System

Authors

  • Muhtadin Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember
  • Ahmad Ricky Nazarrudin Department of Computer Engineering, Institut Teknologi Sepuluh Nopember
  • I Ketut Eddy Purnama Department of Computer Engineering, Institut Teknologi Sepuluh Nopember
  • Chastine Fatichah Department of Informatics, Institut Teknologi Sepuluh Nopember
  • Mauridhi Hery Purnomo Institut Teknologi Sepuluh Nopember

DOI:

https://doi.org/10.23887/janapati.v13i3.84186

Keywords:

Positioning system, Elderly, Smart home, Actuator, Application

Abstract

In 2017, the rate of dependency among the elderly was reported to be at 13.28%, which was problematic, due to the limited number of caregivers to assist them at all times. To address this issue, a robotic service and vital sign-based system were developed, but it was found to be insufficient for monitoring the activities of the elderly. Therefore, this study aimed to address the high dependency rates of elderly individuals who required constant support and care to survive by designing an ultrawideband-based positioning system. The system consisted of five sub-systems, including an indoor positioning system, a database system, a data processing system, an actuator system, and an application user interface. The system testing phase revealed several important findings, including that the position coordinates of the elderly were accurately read with differences of only 98.884 mm and 279.94 under Line of Sight and Non-Line of Sight conditions, respectively. Furthermore, the initial error rate of 164.39% was successfully reduced to only 1.096% by applying the average filter method in the data processing system. The actuator system also showed an impressive accuracy rate of 98% success, while the Android-based application user interface received a high user experience rate of 92.3%. Overall, these findings suggested that the ultrawideband-based positioning system had significant potential to support smart homes for the elderly and improve their quality of life.

References

Badan Pusat Statistik Indonesia, ‘‘Analisis lansia di indonesia 2017,’’ in Statistic Report 1964, 2018.

R. J. Robles and T.-h. Kim, ‘‘Applications, systems and methods in smart home technology: A Review,’’ Int. Journal of Advanced Science And Technology,vol. 15, 2010.

B. P. Statistik, ‘‘Statistik indonesia 2016,’’ 2016.

M. Kessel, M. Werner, F. Gschwandtner, and C. Linnhoff Popien, ‘‘Tracking and navigation for goods and people,’’ Encyclopedia of automotive engineering, pp. 1-12, 2014.

B. OKeefe, ‘‘Finding location with time of arrival and time difference of arrival techniques,’’ 2017.

J. Reed, Introduction to ultra wideband communication systems, an. Prentice Hall Press, 2005.

‘‘Datasheet dwm1000 module.’’ last accessed on May 3, 2019.

H. Lee, J.W. Park, and A. S. Helal, ‘‘Estimation of indoor physical activity level based on footstep vibration signal measured by mems accelerometer in smart home environments,’’ in International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments, pp. 148-162, Springer, 2009.

‘‘Development board wemos d1.’’ last accessed on 3 may 2019.

A. A. N. S. Laksmana, ‘‘Internet of things untuk memantau kondisi serta aktivitas manula menggunakan turtlebot sebagai gateway,’’ 2018.

S. Dengler, A. Awad, and F. Dressler, ‘‘Sensor/actuator networks in smart homes for supporting elderly and handicapped people,’’ in 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW’07), vol. 2, pp. 863-868, IEEE, 2007

J. Foerster, E. Green, S. Somayazulu, D. Leeper, et al., ‘‘Ultrawideband technology for short-or medium-range wireless communications,’’ in Intel technology journal, Citeseer, 2001.

M. Malkauthekar, ‘‘Analysis of euclidean distance and manhattan distance measure in face recognition,’’ 2013.

N. Komiya, M. Tokuoka, R. Egusa, S. Inagaki, H. Mizoguchi, M. Namatame, and F. Kusunoki, ‘‘Novel application of 3d range image sensorto caloric expenditure estimation based on human body measurement,’’in 2018 12th International Conference on Sensing Technology (ICST), pp.371-374, IEEE, 2018.

Cheng Tu, Jiabin Zhang, Zhi Quan, Yingqiang Ding,”UWB indoor localization method based on neural network multi-classification for NLOS distance correction”,

Sensors and Actuators A: Physical, Volume 379, 2024.

Khodjaev, J., Park, Y. & Saeed Malik, A. Survey of NLOS identification and error mitigation problems in UWB-based positioning algorithms for dense environments. Ann. Telecommun. 65, 301–311, 2010.

Alemán, J.J., Sanchez-Pi, N., Garcia, A.C.B. SafeRoute: An Example of Multi-sensoring Tracking for the Elderly Using Mobiles on Ambient Intelligence. In: Bajo, J., et al. Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection. PAAMS 2015. Communications in Computer and Information Science, vol 524. Springer, Cham, 2015.

Guo, Q. Design of a Smart Elderly Positioning Management System Based on GPS Technology. In: J. Jansen, B., Liang, H., Ye, J. (eds) International Conference on Cognitive based Information Processing and Applications (CIPA 2021). Lecture Notes on Data Engineering and Communications Technologies, vol 84. Springer, 2022.

Thakur, Nirmalya, and Chia Y. Han, "Indoor Localization for Personalized Ambient Assisted Living of Multiple Users in Multi-Floor Smart Environments" Big Data and Cognitive Computing 5, no. 3: 42. 2021.

Thakur, Nirmalya and Han, Chia Y., “A Simplistic and Cost-Effective Design for Real-World Development of an Ambient Assisted Living System for Fall Detection and Indoor Localization: Proof of Concept”, 2022.

Jane Chung, Lana Sargent, Roy Brown, “Use of GPS Tracking Technology to Measure Mobility in Older Adults: A Systematic Review, Innovation in Aging”, Volume 4, Issue Supplement_1, 2020

Lin, Xuxin, Jianwen Gan, Chaohao Jiang, Shuai Xue, and Yanyan Liang. "Wi-Fi-Based Indoor Localization and Navigation: A Robot-Aided Hybrid Deep Learning Approach" Sensors 23, no. 14: 6320. 2023.

Martins, H., Gupta, N., Reis, M.J.C.S. ”A Non-intrusive IoT-Based Real-Time Alert System for Elderly People Monitoring”. In: Science and Technologies for Smart Cities. SmartCity360°. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 372. Springer. .2021.

Bibbò, Luigi, Riccardo Carotenuto, and Francesco Della Corte. "An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare" Sensors 22, no. 21: 8119,2022.

Roy, P., Chowdhury, C. “A survey on ubiquitous WiFi-based indoor localization system for smartphone users from implementation perspectives”. CCF Trans. Pervasive Comp. Interact. 4, 298–318, 2022.

Obeidat, H., Shuaieb, W., Obeidat, O. et al. “A Review of Indoor Localization Techniques and Wireless Technologies”. Wireless Pers Commun 119, 289–327, 2021.

M. Kolakowski and B. Blachucki, "Monitoring Wandering Behavior of Persons Suffering from Dementia Using BLE Based Localization System," 2019 27th Telecommunications Forum (TELFOR), Belgrade, Serbia, 2019, pp. 1-4

Kolakowski, Jerzy, Vitomir Djaja-Josko, Marcin Kolakowski, and Katarzyna Broczek. 2020. "UWB/BLE Tracking System for Elderly People Monitoring" Sensors 20, no. 6: 1574

Röbesaat, Jenny, Peilin Zhang, Mohamed Abdelaal, and Oliver Theel. 2017. "An Improved BLE Indoor Localization with Kalman-Based Fusion: An Experimental Study" Sensors 17, no. 5: 951

Leitch, Samuel G., Qasim Zeeshan Ahmed, Waqas Bin Abbas, Maryam Hafeez, Pavlos I. Laziridis, Pradorn Sureephong, and Temitope Alade. 2023. "On Indoor Localization Using WiFi, BLE, UWB, and IMU Technologies" Sensors 23, no. 20: 8598.

Raad, M.W., Sheltami, T., Soliman, M.A., Alrashed, M. (2018). An RFID Based Activity of Daily Living for Elderly with Alzheimer’s. In: Ahmed, M., Begum, S., Fasquel, JB. (eds) Internet of Things (IoT) Technologies for HealthCare. HealthyIoT 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 225. Springer, Cham.

Kim, SC., Jeong, YS. & Park, SO. RFID-based indoor location tracking to ensure the safety of the elderly in smart home environments. Pers Ubiquit Comput 17, 1699–1707 (2013)

Shen, J., Jin, C., Liu, D. (2016). A Survey on the Research of Indoor RFID Positioning System. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10040. Springer.

Obeidat, H., Shuaieb, W., Obeidat, O. et al. A Review of Indoor Localization Techniques and Wireless Technologies. Wireless Pers Commun 119, 289–327 (2021).

Wang, D., Yin, J., Chen, X., et al. (2019). On the use of calibration emitters for TDOA source localization in the presence of synchronization clock bias and sensor location errors. EURASIP Journal on Advances in Signal Processing, Vol.2019 (1), 1-34.

AMJAD I, OMAR A S, ARBAB W A, et al. Mutual coupling reduction using F-shaped stubs in UWB-MIMO antenna[J]. IEEE Access, 2018, 6:2755-2759.

S. Campaña-Bastidas, M. Espinilla-Estévez, and J. MedinaQuero, Review of Ultra Wide Band (UWB) for Indoor Positioning with application to the elderly. [Online]. Available: https://hdl.handle.net/10125/79601

S. K. Gharghan, R. Nordin, A. M. Jawad, H. M. Jawad and M. Ismail, "Adaptive Neural Fuzzy Inference System for Accurate Localization of Wireless Sensor Network in Outdoor and Indoor Cycling Applications," in IEEE Access, vol. 6, pp. 38475-38489, 2018, doi: 10.1109/ACCESS.2018

Geng Chen, Lili Cheng, Rui Shao, Qingbin Wang, Shuihua Wang, A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged: Techniques and Technologies, CMES - Computer Modeling in Engineering and Sciences, Volume 135, Issue 3, 2022,

Downloads

Published

2024-12-01

How to Cite

Muhtadin, Nazarrudin, A. R., Purnama, I. K. E., Fatichah, C., & Purnomo, M. H. (2024). Smart Home for Supporting Elderly Based On Ultrawideband Positioning System. Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI, 13(3), 248–259. https://doi.org/10.23887/janapati.v13i3.84186

Issue

Section

Articles