Scheduling and Predictive Maintenance for Smart Toilet
نویسندگان
چکیده
Modern society needs bathrooms. Poor sanitation is caused by worn-out appliances and expensive cleaning. The technique also requires an inexpensive, dependable sensor. This study had three goals. Creating IoT administration platform the main goal. Literature evaluations assess merits downsides of existing systems. Second, we suggest predictive maintenance to assist predict bathroom equipment breakdowns. Finally, a scheduling algorithm was used determine how many janitors hire. We’ll measure model’s effectiveness make future recommendations. Infrared, temperature humidity sensors create bathroom. Sensors have been studied understand adapt them hygienic private toilet environment. Sensor accuracy cost-effectiveness could be enhanced with more development testing. Auto-Regressive Integrated Moving Average (ARIMA) model accurately predicts time series lags, making it good candidate for maintenance. Long Short-Term Memory (LSTM) in predictions, therefore it’s fair compare two. We use ARIMA handle Remaining Useful Life (RUL) prediction techniques altering (MA) (AR). A genetic janitorial cleaning schedule. proposed schedule workers. approach improves studying soft hard restrictions. Greedy compare. Experimental reveal that suggested ARIGA meets both
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3241942