Advances in Intelligent Nano-Micro-Scale Sensors and Actuators: Moving toward Self-Sustained Edge AI Microsystems

Over recent decades, nano-micro-scale sensors and actuators have evolved from discrete microelectromechanical systems (MEMS) components. As demand for maintenance-free systems grew, developments emphasized integrating energy harvesting into sensing platforms and deploying self-powered sensors that utilize piezoelectric and triboelectric transducers. Such co-localization enabled self-sustained Internet-of-Things (IoT) deployments, supporting continuous operation without external power and improving network autonomy and scalability. Integrating artificial intelligence (AI) at the sensor edge has further transformed these platforms into intelligent AI-of-Things (AIoT) systems, enabling multimodal analytics, adaptive decision-making, and immersive human-machine interaction. Concurrently, advances in photonics-including mid-infrared, terahertz, and near-infrared technologies-have produced sensitive molecular and chemical sensors with improved selectivity and spectral resolution. These advances have also yielded photonic integrated circuits capable of ultrafast in-sensor computation and real-time Bayesian photonic neural inference, delivering sophisticated edge-AI processing with low latency and power consumption. Hybrid systems that combine flexible wearable electronics with integrated photonic platforms have emerged, allowing direct transduction and interpretation of mechanical and physiological signals from flexible sensors via photonic chips. Progress in materials, packaging, and system co-design underpins reliability and operation in harsh environments. Together, these advances foreshadow highly integrated, self-sustained edge-AI microsystems that embody perpetual, real-time intelligence and seamless user-environment interaction.