Human beings comprehensively perceive the world through the integration of multiple senses such as touch, vision, hearing, taste, and smell. This sensory integration not only helps us understand the environment, but also provides key information for coping with various situations. With the advancement of technology, the development of humanoid robots and human-machine interfaces highlights the urgent need to expand human sensory functions. This demand is not limited to the traditional five senses, but may also introduce a sixth sense beyond these senses: remote perception. Remote sensing, as an important breakthrough in the cognitive field, demonstrates enormous potential in enhancing decision-making ability and environmental interaction. By breaking through the limitations of traditional senses, remote perception has opened up new possibilities for human perception and cognition.However, current electronic skin sensors mainly rely on physical contact to obtain information, which shows significant shortcomings in the absence of direct interaction, limiting the ability of human-machine interaction (HMI). Although there has been research on non-contact or pre contact sensing technology, further development and exploration of remote sensing technology are still relatively limited. To address these challenges, researchers have begun to focus on enhancing the non-contact sensing capability of sensors through innovative surface structure design, introduction of new composite materials, and ion implantation.However, the charge capture capability of the dielectric layer is still insufficient, which affects the overall sensitivity of the sensor and makes it more difficult to achieve effective sensing without direct contact. On the other hand, although simulation modeling techniques relying on big data can recognize three-dimensional shapes, the sensitivity of existing inductors still cannot simultaneously recognize the shape and material composition of objects. Therefore, integrating advances in materials science, nanotechnology, and deep learning algorithms into advanced sensor design is crucial for enhancing tactile and remote sensing capabilities. Improving charge capture capability is the key to promoting further development of remote sensing technology. Remote sensing, as an emerging technology, can detect and distinguish the shape and material composition of objects within a certain distance, demonstrating broad application prospects.