Two-dimensional photosensor arrays for motion detection systems

IF 7.1
Chip Pub Date : 2026-06-01 Epub Date: 2025-09-15 DOI:10.1016/j.chip.2025.100166
Jing Chen , Tian-Ling Ren , Lin Han
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引用次数: 0

Abstract

Motion detection systems are pivotal in numerous technological domains, from security surveillance to autonomous navigation, offering real-time responsiveness to dynamic environments. Motion detection systems are essential for the development of artificial intelligence machine vision systems. Two-dimensional (2D) material–based photosensors possess ultrafast photoresponsivity, which has heralded a transformative era in motion detection capabilities, enhancing both spatial and temporal resolution, predicting their potential in accurate motion detection systems. Recently, photosensor arrays based on 2D materials have been used for accurate motion detection, indicating their prospects in future artificial intelligence machine vision systems. Here, we review the state-of-the-art motion detection systems based on 2D photosensors arrays, mainly including motion-edge computing, and motion-direction computing. Key findings from the examination of state-of-the-art technologies demonstrate significant strides in reducing system latency, power consumption, and the overall computational load by internalizing processing within the sensor domain. We provide comprehensive views of the merits and drawbacks of the 2D motion detection systems, projecting an optimistic future for compact and efficient motion detection systems. Finally, we discuss the opportunities, progress, and challenges of 2D materials in motion-detection-system applications.
用于运动检测系统的二维光敏传感器阵列
运动检测系统在许多技术领域都是关键,从安全监控到自主导航,提供对动态环境的实时响应。运动检测系统对于人工智能机器视觉系统的发展至关重要。基于二维(2D)材料的光传感器具有超快的光响应性,这预示着运动检测能力的变革时代,提高了空间和时间分辨率,预测了它们在精确运动检测系统中的潜力。近年来,基于二维材料的光敏传感器阵列已被用于精确的运动检测,表明其在未来人工智能机器视觉系统中的前景。本文综述了基于二维光电传感器阵列的运动检测系统,主要包括运动边缘计算和运动方向计算。对最先进技术的研究结果表明,通过将传感器域内的处理内部化,在降低系统延迟、功耗和总体计算负载方面取得了重大进展。我们提供了二维运动检测系统的优点和缺点的全面观点,预测一个乐观的未来,紧凑和高效的运动检测系统。最后,我们讨论了二维材料在运动检测系统应用中的机遇、进展和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.80
自引率
0.00%
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