A Smart Lamp Design Scheme for Myopia Prevention based on 3D Eye Positioning Model

The evolution of lighting technology has markedly shifted its focus from durability to superior control performance. Modern lighting systems now prioritize advanced features such as the adaptive dimming, color temperature adjustment, and occupancy sensing, superseding traditional emphasis on durability. This paradigm shift enables more efficient energy utilization, significantly improves user experience, and enhances ambient settings. Inspired by this, this research study presents an innovative lighting design framework that attempts to prevent myopia development through a tailored approach. The proposed methodology includes a state-of-the-art 3D eye localization model that optimizes lighting conditions and minimizes the likelihood of myopia progression. Utilizing state-of-the-art sensor technologies and algorithmic techniques, the proposed system tracks and meticulously examines eye orientation in real time and provides customized lighting parameters for each individual. By leveraging these advanced features, the proposed design scheme offers a breakthrough solution that not only enhances visual comfort but also protects eye health. For testing the performance, the ground truth datasets are annotated, and the detection accuracy rate is selected as the metric for evaluation. The proposed algorithm is compared with traditional Support Vector Machine (SVM) and Firebase Cloud Messaging (FCM) algorithms. It is evident that the proposed model can effectively detect the eye's position.