Intelligent Basketball Dribble Trajectory Monitoring Based on Data-Driven Technology

Abstract

Data-driven technology is a problem-solving method, starting from the initial data or observations, using heuristic rules to find and establish the relationship between internal features, to discover some theorems or laws. With the sharp increase in the number of basketball players, there are increasingly studies on the dribbling action of its trajectory and placement. Data-driven technology usually also refers to natural language processing methods based on large-scale statistical data. This paper proposes to use this technology to monitor the trajectory of basketball dribbling, which can more effectively reduce the pain caused by improper dribbling when teenagers play basketball, and can also more effectively improve a shooting percentage. The invention also relates to the field of Internet of Things technology, moving target detection, and the algorithm of target movement trajectory. The Internet of Things technology originated in the media field and is the third revolution in the information technology industry. The Internet of Things refers to the connection of any object with the network through the information-sensing equipment and according to the agreed protocol, and the objects exchange and communicate information through the information dissemination medium to realize intelligent identification, positioning, tracking, supervision, and other functions. After that, a lot of experiments were carried out, and the results showed that the number of breakthroughs after using this technology accounted for 30%, and the hit rate after the breakthrough was also above 70%. The TFHBase system and its optimization strategy are efficient and can effectively solve the problem of basketball trajectory monitoring, and we also do some exploration on trajectory visualization, to further control the landing point of the basketball trajectory.