Infrared scanning systems have emerged as an effective solution for detecting physical contact with surfaces. These systems typically consist of infrared transmitters and receivers installed on opposite edges of a plane, aligned to face each other. Conventionally, such systems utilized a one-to-one configuration—each transmitter paired with a specific receiver—enabling quick response and straightforward system design. However, this setup suffers from a key drawback: the inability to detect multiple contact points at the same time. To overcome this limitation, the one-to-many scanning approach has been introduced. In this method, a single transmitter sends out infrared signals that are simultaneously received by multiple detectors on the opposing side. This allows the system to analyze real-time signal disruptions to estimate both the position and size of contacting objects. Recent advances in computational power have significantly enhanced the speed and accuracy of this method. Nevertheless, its application has largely remained confined to flat surfaces, and there has been a lack of theoretical tools for evaluating performance across diverse sensor arrangements and surface geometries. In response to this gap, our study presents a mathematical model of an infrared sensor array system, enabling predictive analysis of performance across various sensor placements on both planar and curved surfaces. Furthermore, we investigate how positional deviations, including misalignments in sensor orientation, impact detection accuracy, which offers a robust framework for quantitatively predicting system performance and will serve as a valuable tool for designing customized sensor configurations for a wide range of future applications.
목차
Abstract 1. Introduction 2. LED Simulation 3. Scanning Mesh Net 3.1 Blocking Function 3.2 Touch Pixel 4. Conclusion Acknowledgement References