Big data analytics from a wastewater treatment plant

Abstract

Wastewater treatment plants (WWTPs) use considerable workforces and resources to meet the regulatory limits without mistakes. The advancement of information technology allowed for collecting large amounts of data from various sources using sophisticated sensors. Due to the lack of specialized tools and knowledge, operators and engineers cannot effectively extract meaningful and valuable information from large datasets. Unfortunately, the data are often stored digitally and then underutilized. Various data analytics techniques have been developed in the past few years. The methods are efficient for analyzing vast datasets. However, there is no wholly developed study in applying these techniques to assist wastewater treatment operation. Data analytics processes can immensely transform a large dataset into informative knowledge, such as hidden information, operational problems, or even a predictive model. The use of big data analytics will allow operators to have a much clear understanding of the operational status while saving the operation and maintenance costs and reducing the human resources required. Ultimately, the method can be applied to enhance the operational performance of the wastewater treatment infrastructure.