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Traffic management is one of the challenging issues that need to be addressed by any urban area and the need to employ traffic measures is imperative. In any kind of traffic monitoring system, vehicle detection and counting are basic functionalities. In this paper, a YOLO-based model is utilized in the counting of tricycles, which is a unique kind of public transportation in the city of Tagbilaran, located in the province of Bohol, Philippines. The said model is used as the object detection model, which is integrated in the module that imports the Simple Online and Realtime Tracking (SORT) algorithm. Data collected are saved in .csv files which are then manually processed to generate a graph representation of the traffic status. Results in the tricycle count reveal that vehicles are minimal during mid-morning or late afternoon. Furthermore, the counting module was tested for performance where a value of 59.34 counting percentage was generated. This was based on the percentage of the automatic count compared to the manual count of the ground truth. A continuous enhancement in tracking the tricycles is recommended. The inclusion of various angles when counting vehicles going to different directions in the videos may generate a more practical data that will support any traffic reduction initiative. Likewise, traffic conditions such as weather and possible occlusions should be considered in the study for practical reasons.