<p>This study explores recent advancements in viscometry techniques for precise viscosity measurements, focusing on automating the widely used Ubbelohde capillary viscometer. Previous attempts at automation utilising single-camera and infrared laser techniques demonstrated initial promise; however, these approaches exhibited significant limitations. This research introduces the design and validation of a new automated kinematic capillary viscometer system utilising real-time computer vision for simultaneous meniscus detection and timing up to three viscometers. The system incorporates two waterproof cameras per Ubbelohde viscometer connected to a computer running custom-made ViscoCheck software, with temperature control managed by an Arduino microcontroller. It maintains the water bath temperature within ± 0.5&#xa0;°C and measures flow time with ± 0.01&#xa0;s resolution. The system was validated by measuring the viscosity of a binary ethanol–hexane mixture across the entire mole fraction range at a constant pressure of 101.325&#xa0;kPa and a temperature of 298.15&#xa0;K. Results were compared with literature values and correlated using the Grunberg–Nissan (G–N) and McAllister three-body models. Excess molar volumes (<i>V</i>^<i>E</i>) and viscosity deviations (<i>Δƞ</i>) were calculated to assess accuracy in capturing complex liquid mixture behaviour. Findings revealed general agreement between experimental and reference data. The G–N model showed excellent agreement, exhibiting a low standard deviation (0.036) and absolute average deviation (1.648%). These results demonstrate the system's potential as a reliable tool for precise automated viscosity measurements across various industrial applications.</p>