Developing Innovative Elderly Care to Find Pathways Home Using Artificial Intelligence Techniques
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Abstract
This research aims to 1) develop innovation for elderly care to find pathways home using artificial intelligence techniques, and 2) evaluate the effectiveness and satisfaction of the developed innovation. The innovation consists of two parts: the front-end uses Flutter as the framework for user interface development, and the back-end uses Python to process data and create APIs that connect to a MySQL database. The system focuses on storing elderly individuals’ data and using artificial intelligence techniques to analyze and compare facial data captured through the mobile application. After analyzing the facial verification results, the system searches for data to help guide elderly individuals back home. It uses Principal Component Analysis (PCA) and Support Vector Machine (SVM), which are machine learning algorithms known for their effectiveness in classifying high-dimensional data. The research instruments include a questionnaire and the developed innovation system. Data were analyzed using descriptive statistics: frequency, percentage, mean, and standard deviation. The results show that (1) the system displays personal information and home coordinates accurately, with a face recognition accuracy of 89%, and (2) the performance evaluation by five experts shows that the system performs at a high level (mean = 4.31, SD = 0.34). Additionally, the user satisfaction evaluation results from a purposive sample of 33 participants showed that the satisfaction level with the developed system was at a high level (mean = 4.36, SD = 0.45)
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