An Intelligent Mobile Application to Monitor the Availability of Tennis Courts using Machine Learning and Object Detection


Harry Su1 and John Morris2, 1USA, 2California State Polytechnic University, USA


Acemind aims to address the lack of real-time tennis court availability information, enhacing player experience, promoting community well-being, and making sports easily accessible to not only the wealthy [1]. The technology utilizes Raspberry Pi computers with Pi cameras to record live footage, Firestore Database to store information regarding court status, and a front-end mobile application made with flutter to display information to users [2]. Key challenges include running object detection model, YOLOv5, on the computer seamlessly with the camera, which was solved by adjusting libraries' versions appropriately and ensuring the proper installation of all packages [3]. The mobile application also struggled to display the correct court's information, but the problem was fixed with a setState function that updates the bottom popup widget using a variable. During experimentation, YOLOv5 consistently identified humans among distractions commonly found near tennis courts even under suboptimal conditions, proving its resilience to unwanted challenges in inputs [4]. Although Acemind has limitations such as the need of a cellular connection and government permission, it is useful as it presents valuable court information regarding availability without the shortcomings of smart tennis courts and tennis maps, bridging the inequality gap by providing everybody a change to play.


Tennis, AI, Community, Convenience

Full Text  Volume 14, Number 4