Predictive Optimization of Energy Consumption in Drinking Water Systems Using Parallel Algorithms

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Nombre IEEEACCESS_01_2026_ENG_AUDIO.m4a
Autor Jose Vicente Berná Martinez
Título Predictive Optimization of Energy Consumption in Drinking Water Systems Using Parallel Algorithms
Resumen Optimising energy consumption has become a priority objective for companies and organisations, especially in essential services such as drinking water supply. Traditional strategies of maximising water storage generate energy inefficiency by forcing pumps to move large masses of water. These strategies also generate other negative effects, such as water loss in case of incidents and stress on aquifers. The problem addressed is the need to optimise the operation of drinking water production plants, seeking a balance between minimising stored water, guaranteeing supply and reducing energy consumption. Traditional optimisation systems have limitations in the number of variables they can handle and in the search for solutions in large search spaces. The optimisation problem is the search for solutions in an immense and computationally intractable data space. In this work, a new algorithm based on predictive artificial intelligence and the search for optimal values in distributed and parallel data spaces is proposed... - Proyecto PID2023-152566OB-I00 - "Mantenimiento preventivo de infraestructuras digitales mediante la aplicación de Inteligencia Artificial para el diagnóstico y predicción de anomalías (PreMAI)". Financiado por MICIU/AEI /10.13039/501100011033 y por FEDER, UE
Duración 00:05:04.00
Keywords PremAI, Infraestructuras críticas, Detección Anomalías, Inteligencia Artificial
Usuario jvberna[perdoname]ua.es
Tipo AUDIO
Visitas 4
Tamaño 4.64MB