Enhanced ARIMA Model for Water Demand Forecasting in Smart Water Distribution Network
Keywords:
accurate, validated, ARIMA, consumption, forecastingAbstract
The fraction of the world's freshwater resources that are usable each year decreases. A poll conducted by the World Economic Forum predicts that during the next two decades, there will be severe water shortages all across the world due to rising demand. It is difficult to both stop the rising demand for water and cut down on the amount of water that is wasted in transit. Cities are increasingly adopting IoT-enabled water distribution systems that employ smart water meters to collect real-time data on water consumption and transfer it either to the cloud, fog, or edge. Then it can be stored, analysed for patterns, and used to plan for future water needs and create more effective infrastructure. It's crucial to anticipate and analyse client demand for water use. The enhanced auto-regressive integrated moving average (ARIMA) method is used to analyse the trend of water consumption data and forecast future water consumption demand based on previous historical information. When compared to other forecasting methods, they tend to provide better results. It is important to have an accurate forecast of water use. Planning and building water supply systems rely heavily on accurate and dependable forecasts. The ARIMA model was validated using the mean absolute scaled error (MASE) and root mean square error (RMSE).
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