Avoidance of operational sampling errors in drinking water analysis
This 2022 journal article published in AQUA – Water infrastructure, Ecosystems and Society sees Fernandes et al. presenting a computerized “system for reporting and learning from adverse events” in water sampling and analysis laboratories. The work was prompted by “a high frequency of adverse events in connection with sampling” at the Water Laboratory of Santiago do Cacém Municipality in Portugal. After introducing the topic of water quality testing and work related to using artificial intelligence (AI) in that testing, the authors describe their method of using a Eindhoven Classification Model (ECM) within the scope of ISO/IEC 17025 requirements. They then discuss the results of their software-based approach and conclude that their modular adverse event reporting and learning system has many strengths, particularly in that it “allows knowledge extraction, i.e., the identification of the main failure causes, possible trends, areas requiring improvement plans, or changes in procedures.”
