As a key physical quantity of environmental monitoring, humidity plays an irreplaceable role in agricultural production, health monitoring and extreme environmental detection. However, the limitations of traditional humidity sensing systems in response speed, environmental adaptability, and information analysis capabilities have made it difficult to meet the high-order requirements of modern applications for real-time, reliability, and intelligence. This bottleneck is driving a profound change in humidity sensing technology—its development focus has shifted from the improvement of single device performance to the construction of intelligent sensing systems with information understanding and autonomous decision-making capabilities. This perspective paper outlines the evolution path of humidity sensing technology from manufacturing to intelligent sensing. Firstly, the performance boundary of humidity sensor devices based on different humidity sensitive materials is analyzed. Furthermore, the technical trend of constructing intelligent sensor nodes through system integration is discussed, and the enabling mechanism of artificial intelligence algorithm in realizing intelligent applications such as health monitoring, human-computer interaction and intelligent agriculture is emphatically explained. Finally, the current challenges in sensitivity, stability, power consumption and signal analysis are pointed out, and the future development opportunities are prospected, in order to provide theoretical support and technical path for promoting the transition of humidity sensing from detection to cognition.

Neuromorphic computing systems can perform memory and computing tasks in parallel on artificial synaptic devices through simulating synaptic functions, which is promising for breaking the conventional von Neumann bottlenecks at hardware level. Artificial optoelectronic synapses enable the synergistic coupling between optical and electrical signals in synaptic modulation, which opens up an innovative path for effective neuromorphic systems. With the advantages of high mobility, optical transparency, ultrawideband tunability, and environmental stability, graphene has attracted tremendous interest for electronic and optoelectronic applications. Recent progress highlights the significance of implementing graphene into artificial synaptic devices. Herein, to better understand the potential of graphene-based synaptic devices, the fabrication technologies of graphene are first presented. Then, the roles of graphene in various synaptic devices are demonstrated. Furthermore, their typical optoelectronic applications in neuromorphic systems are reviewed. Finally, outlooks for development of synaptic devices based on graphene are proposed. This review will provide a comprehensive understanding of graphene fabrication technologies and graphene-based synaptic device for optoelectronic applications, also present an outlook for development of graphene-based synaptic device in future neuromorphic systems.