Multi-Layer Perceptron Neural Network and Internet of Things for Improving the Walking Stick with Daily Travel Surveillance of Suburban Elderly
How to Cite?
Sumitra Nuanmeesri, Lap Poomhiran, "MultiLayer Perceptron Neural Network and Internet of Things for Improving the Walking Stick with Daily Travel Surveillance of Suburban Elderly," International Journal of Engineering Trends and Technology, vol. 69, no. 12, pp. 317-327, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I12P235
Many countries are entering the era of the elderly, causing the population of the elderly to increase steadily. However, these elderly people still want to be self-reliant, especially walking anywhere without needing a caretaker. Thereby, the walking sticks have become a daily tool to support and walk for the elderly. This paper proposed improving the walking stick as an intelligent cane that is a walking aid and monitoring tool for the daily travel surveillance of suburban elderly in Thailand. The intelligent cane’s daily travel surveillance forecasting model was built by applying the Multi-Layer Perceptron Neural Network. Further, the performance of the model accuracy was enhanced by synthesizing imbalanced data based on Synthetic Minority Over-sampling Technique. The effectiveness of the model showed that the prediction accuracy was 96.89%, the precision was 97.62%, the recall was 98.80%, and F-measure was 98.21%. Moreover, the developed intelligent cane architectures allow their family to monitor, track and communicate with the elderly using the Internet of Things technology and real-time camera by remote control via the mobile application. As a result, this work showed that the suburban elderly could perceive, learn, and appreciate the recent technology necessary for their life.
Elderly, Internet of Things, Multi-Layer Perceptron Neural Network, SMOTE, Walking stick.
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