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Near-Sensor Edge Computing System Enabled by a CMOS Compatible Photonic Integrated Circuit Platform Using Bilayer AlN/Si Waveguides

Authors: Zhihao Ren; Zixuan Zhang; Yangyang Zhuge; Zian Xiao; Siyu Xu; Jingkai Zhou; Chengkuo Lee

DOI: 10.1007/s40820-025-01743-yStatus: Verified Translated Edition
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Key Findings in This Report

• A novel near-sensor edge computing system integrates AlN microrings for photonic feature extraction and Si Mach–Zehnder interferometers for photonic neural network operations, achieving real-time AI processing. • Demonstrates high classification accuracy (96.77% for gestures, 98.31% for gaits) with low latency (<10 ns) and minimal energy consumption (<0.34 pJ). • Enables low-power, high-speed AI applications with seamless hybrid photonic-electronic integration on a bilayer AlN/Si waveguide platform. • Bridges the gap between AI models and real-world applications, enabling efficient, privacy-preserving AI solutions for healthcare, robotics, and next-generation human–machine interfaces.