Two-phase PT-Topk Query Processing Algorithm for Uncertain IOT Data in Dam Safety Monitoring

Economic, Environmental and Social Gains of the Implementation of Artificial Intelligence at Dam Operations toward Industry 4.0 Principles

“…Another economic evidence is the reduction on overtime made by operational crews, once they do not need to extend their working shifts anymore. The aforementioned result corresponds with Mao et al [22] research which identified a multiplication of imprecise data and proposed an efficient processing algorithm PT-Top K biphasic, capable of select monitoring data for dam safety, reducing transmission costs by 87.5%. It was a reaction time gain up to 54.5% faster in this transmission.…”

“…Furthermore, the development of IoT tools for dam safety monitoring that identify and eliminate data potentially out of range, resulted in a reduction of 87.5% on transmission costs and lower response time by 54% comparing to centralized processing data algorithms [22]; The information security system that improves safety on IT infrastructure of hydropower plant dam by detecting errors on network configuration paths and giving prompt answer to cyber-attacks [14]; The impact assessment of multiple gates integration that resulted in lower levels of water in reservoirs and water quality [39]; An optimization model to reach a reduction of water flow peaks, considering all possible scenarios and a faster operation response time [17]; The integration of IoT and Big Data to increase safety at a reservoir [40].…”

“…The article of Russel [21] is just one of a few studies that take into account economic gain using fuzzy logic to optimize a hydropower plant. In Mao et al [22] an algorithm was developed to filter and select information from a large database, related to monitoring a water dam. Sordo-Ward et al [23] and Sulis et al [24] sought to understand variables that are related to a reservoir and identified sludges behavior and chemical wastes influencing dam operations.…”