Editorial
Building an Intelligent Home Perception System Based on Multi-Modal Information Interaction
@ARTICLE{10.4108/eetsis.10349, author={Guo Zhanmiao and Qian Zhongli}, title={Building an Intelligent Home Perception System Based on Multi-Modal Information Interaction}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={12}, number={8}, publisher={EAI}, journal_a={SIS}, year={2026}, month={3}, keywords={}, doi={10.4108/eetsis.10349} }- Guo Zhanmiao
Qian Zhongli
Year: 2026
Building an Intelligent Home Perception System Based on Multi-Modal Information Interaction
SIS
EAI
DOI: 10.4108/eetsis.10349
Abstract
In response to the problems of single interaction modality and weak perception ability in traditional smart homes, this paper proposes a multi-modal information perception Artificial Intelligence(AI) model invocation framework. It schedules visual, voice, and sensor data through natural language prompts, and combines the zero-shot visual recognition method of the cloud-based visual-language hybrid large model workflow to achieve cross-scene generalization ability without labeled training. This framework can innovatively solve the problems of heterogeneous data fusion and insufficient computing power of edge devices. Experimental results show that the multi-modal smart home perception system designed in this paper achieves an accuracy rate of over 90% in environmental perception and a precision rate as high as 92% in user intention recognition, which can provide new ideas and practical foundations for the multi-modal perception of future smart home technology.
Copyright © Guo Zhanmiao et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
