A Study on Artificial Intelligence-Based Sand Filtration Backwash Cycle Determination Method for Improving Sand Filtration Process Maintenance Performance

Extended Abstract Increased workload and aging of water treatment maintenance personnel can hinder the supply of quality drinking water and threaten national water security. At the present time, in the age of low birth rate and aging population, and the era of the 4th industrial revolution, the artificial intelligence-based water treatment facility operation system is evaluated as a future technology that can continuously produce water necessary for people's lives. The artificial intelligence-based water treatment facility operation system is expected to increase the economic feasibility and production efficiency of water treatment facility operations by applying it to ICT/IOT/CPS-based smart water treatment facilities. The sand filtration process constituting the water treatment facility can remove aggregated suspended matter through the gaps between filter media, and periodic backwashing must be performed to maintain performance. The water treatment facility operates backwashing based on the water level according to the rise in the water level due to clogging of the filter media. However, since the increase in the water level is measured after the filter media has already been clogged, it is difficult to assert that the performance of the sand filter facility is restored to close to 100% as a result of backwashing. This can increase the workload of facility maintenance personnel by advancing filter media replacement cycles. Therefore, in this study, a