Multimodal Intelligent Flooring System for Advanced Smart‐Building Monitoring and Interactions

The floor constitutes one of the largest areas within a building with which users interact most frequently in daily activities. Employing floor sensors is vital for smart‐building digital twins, wherein triboelectric nanogenerators demonstrate wide application potential due to their good performance and self‐powering characteristics. However, their sensing stability, reliability, and multimodality require further enhancement to meet the rapidly evolving demands. Thus, this work introduces a multimodal intelligent flooring system, implementing a 4 × 4 floor array for multimodal information detection (including position, pressure, material, user identity, and activity) and human–machine interactions. The floor unit incorporates a hybrid structure of triboelectric pressure sensors and a top‐surface material sensor, facilitating linear and enhanced sensitivity across a wide pressure range (0–800 N), alongside the material recognition capability. The floor array is implemented by an advanced output‐ratio method with minimalist output channels, which is insensitive to environmental factors such as humidity and temperature. In addition to multimodal sensing, energy harvesting is co‐designed with the pressure sensors for scavenging waste energy to power smart‐building sensor nodes. This developed flooring system enables multimodal sensing, energy harvesting, and smart‐sport interactions in smart buildings, greatly expanding the floor sensing scenarios and applications. The multimodal intelligent flooring system can realize the simultaneous detection of position, pressure, and material information, as well as interactive energy harvesting with a minimalist interconnection design. After the integration with neural networks, the multimodal intelligent flooring system achieves the recognition functionalities of user identity and motion, enabling the fusion of multimodal sensing and intelligent interactions in smart‐building applications.