Automated Liquid-Level Monitoring and Control using Computer Vision
2020
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
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