Smart Wardrobe System Based on Weather Prediction for Visually Impaired Users Using the Sugeno Fuzzy Method
DOI:
https://doi.org/10.33795/jartel.v16i2.9099Keywords:
BMKG API, Fuzzy Sugeno, Internet of Things (IoT), Smart Wardrobe, Visually ImpairedAbstract
Visually impaired individuals face difficulties in selecting appropriate clothing according to daily weather conditions, often relying on the help of others. This dependency can reduce their independence in daily activities. This research aims to design and build a "Smart Wardrobe System" that can provide automatic clothing recommendations based on weather predictions to enhance the independence of visually impaired users. The system is developed based on the Internet of Things (IoT) using an ESP32 microcontroller to retrieve real-time weather data from the BMKG API, including parameters of temperature, humidity, wind speed, and rainfall. The Fuzzy Sugeno method is implemented to process this data and generate a decision for clothing recommendations. To ensure accessibility, the system provides output in the form of voice instructions through a DFPlayer Mini module as well as physical action by automatically opening the relevant clothing drawer using a solenoid lock. The test results show that the Fuzzy Sugeno method successfully provided logical recommendations with an accuracy rate of 94.74% based on test scenarios. This prototype proved effective in providing accessible and actionable recommendations, thereby having the potential to increase the daily independence of visually impaired users.
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