Advancing Wastewater Treatment: Harnessing LiDAR Technology for Enhanced Monitoring, Optimization, and Environmental Impact Reduction

Abstract This paper outlines the use of LiDAR technology for visualizing aeration basins in wastewater treatment facilities to improve the sustainability of wastewater treatment in general. Previous studies have either focused mostly on technical challenges related to the use of LiDAR, or on maintenance issues separately. The goal of this study was a novel integration of the use of high resolution spatial data with on-line process control and machine learning methods to optimize operations. Further, the development of a framework to link spatial data collected with LiDAR, and operational parameters, through the maintenance transferal from timed-based to condition-based. This had the potential to not only reduce maintenance costs, and risk of unplanned downtime, but also minimizing energy use while increasing aeration efficiency. A case study resulted in the early discovery diffuser misalignments and play in aeration sediment build-up for an extended service life. Analysis indicated an improvement in oxygen transfer, lower greenhouse gas emissions, and better effluent quality. Although there were challenges in data integration, and adoption of LiDAR, the study developed meaningful solutions for these challenges. In conclusion, this study indicated that spatial sensing integrated with predictive analytics modernized the wastewater treatment industry to be smarter, cleaner, and more sustainable.