Pak Hon Li¹ and Yujia Zhang², ¹USA, ²California State Polytechnic University, USA

Ensuring child safety around swimming pools remains a paramount concern for parents and caregivers [4]. In this research, we present an innovative child safety system that leverages advanced computer vision technology and mobile app integration. Our system employs the YOLOv5 object detection model to continuously monitor swimming pool areas for the presence of children [5]. Upon detection, it promptly sends real-time alerts to parents' mobile apps, allowing for proactive supervision and accident prevention. We conducted two experiments to evaluate the system's performance: one focused on the object detection model's accuracy, achieving high precision and recall rates of 93.5% and 82.2%, respectively, while the other assessed the system's real-world applicability and mobile app functionality [6]. The results indicate robust child detection capabilities and reliable alerting mechanisms. By addressing limitations such as environmental factors and usability, our project strives to enhance child safety near swimming pools, offering a valuable contribution to the field of safety technology [7].

Child Safety, Computer Vision, Mobile App, Object Detection