In this paper, a novel approach to tracking the movement of objects is introduced within slim glass tubes filled with water using advanced image processing techniques. For this study, the YOLOv8 model was used for object identification, while motion tracking used the ByteTrack model; these models are particularly prepared to address challenges that may arise in strictly restricted tube space. Because it has use YOLOv8 for detecting objects within each frame of the video and ByteTrack for continuous tracking along the entire motion of an object in the sequence, the approach combines respective strengths in precision detection and reliable motion track in a challenging operating environment where a fluid medium comes combined with space constraints. It applies the method to video data of the movement of objects through the tube captured and scrutinized frame by frame as the objects’ path and behavior are well examined. From the recorded movement data, the findings are greatly informative regarding the dynamics of moving objects through water. The transition behavior studied at the falling object’s descending speed indicates major behavioral characteristics, providing deeper insight into fluid dynamics in confined environments. This methodology improves precision and reliability more than the traditional approach but also offers exciting possibilities for fluid dynamics study as well as its industrial applications when dealing with small-scale liquid systems. Results obtained open new perspectives in the design and operation of systems relying on the precise positioning of objects in liquid mediums, particularly in the fields of biomedical devices, chemical processing, and flow analysis in engineering applications.