Automated Liquid-Level Monitoring and Control using Computer Vision

Chemists spend an inordinate amount of time performing low-level tasks based on visual observation. Camera-enabled laboratory equipment in conversation with computer vision algorithms can be used to automate many of these processes, thereby freeing up valuable time and resources. We developed a generalizable computer-vision based system capable of monitoring and controlling liquid-level across a variety of chemistry applications. This paper reports on the system’s motivation, architecture, and successful deployment in three experimental use cases which require continous stirring: continuous preferential crystallization (CPC), slurry filtration, and solvent swap distillation