Smart home monitoring systems are essential for home security. Creating monitoring devices that are intrusion-resistant, scalable, and environment-compatible remains a challenge. In this study, we have developed a soft, warm, and mass-producible triboelectric carpet fabric for motion monitoring and user recognition. A specifically designed conductive chenille yarn is utilized as the inlay yarn, which is inserted into the highly elastic 1 × 1 rib courses using knitting weft inlay technology to produce the chenille triboelectric carpet fabric. The carpet fabric generates a maximum power density of about 2942 μW/m2 in the contact-separation mode, which could power small electronic devices by harvesting energy using simple circuit management. Additionally, it can be used for behavior recognition and user identification with the support of machine learning. Four behaviors including slow walking, walking, jogging and jumping are classified successfully, and four different subjects are recognized. The carpet fabric is flexible, warm, inexpensive, easy to manufacture, and compatible with the living environment, showing great potential in smart monitoring systems for home security. Display omitted •Development of a scalable, comfortable, and warm triboelectric chenille carpet fabric.•Successful identification of diverse behaviors and individuals combined with machine learning.•Promising solution for enhancing home security monitoring.