A critical review of the data pipeline: how wastewater system operation flows from data to intelligence
Author(s) -
Jean-David Therrien,
Niels Nicolaï,
Peter A. Vanrolleghem
Publication year - 2020
Publication title -
water science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.406
H-Index - 137
eISSN - 1996-9732
pISSN - 0273-1223
DOI - 10.2166/wst.2020.393
Subject(s) - raw data , computer science , pipeline (software) , bridge (graph theory) , resource (disambiguation) , work (physics) , state (computer science) , risk analysis (engineering) , data science , computer security , systems engineering , engineering , business , medicine , mechanical engineering , computer network , algorithm , programming language
Faced with an unprecedented amount of data coming from evermore ubiquitous sensors, the wastewater treatment community has been hard at work to develop new monitoring systems, models and controllers to bridge the gap between current practice and data-driven, smart water systems. For additional sensor data and models to have an appreciable impact, however, they must be relevant enough to be looked at by busy water professionals; be clear enough to be understood; be reliable enough to be believed and be convincing enough to be acted upon. Failure to attain any one of those aspects can be a fatal blow to the adoption of even the most promising new measurement technology. This review paper examines the state-of-the-art in the transformation of raw data into actionable insight, specifically for water resource recovery facility (WRRF) operation. Sources of difficulties found along the way are pinpointed, while also exploring possible paths towards improving the value of collected data for all stakeholders, i.e., all personnel that have a stake in the good and efficient operation of a WRRF.
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