Smart Solutions for Safer Water: Integrating Machine Learning into the Inspection and Optimization of Treatment Facilities

August-Wilhelm Scheer Institut, Uni Campus D 5 1, Saarbrücken, Germany

^* Corresponding author: marie.niederlaender@aws-institut.de

Abstract

Ensuring the effective treatment of wastewater is essential for the safety of people and the environment, as the discharge of contaminated water into natural waters has disastrous consequences. In Germany and other European countries, the number of trained professionals in the field of wastewater treatment plant (WWTP) operation is constantly decreasing, which is why the optimization and inspection of WWTPs is a relevant field for the application of innovative approaches such as artificial intelligence and machine learning. This study provides an overview of the current progress in the application of machine learning from different perspectives relevant to WWTPs and other critical infrastructure. The perspectives include critical infrastructure monitoring, optimization of treatment processes, monitoring of water bodies and WWTP inspection. In addition, a concept for an automated, AI-based remote inspection system for rural WWTPs using a cloud edge approach and intelligent camera systems is presented for performing daily plant inspection tasks and detection of critical events.