A Movable Waste Classification System Based on Human-Computer Interaction Technology

Yuyan Zhu

doi:10.47297/taposatWSP2633-456930.20260705

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A Movable Waste Classification System Based on Human-Computer Interaction Technology

7卷第5期

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A Movable Waste Classification System Based on Human-Computer Interaction Technology
A Movable Waste Classification System Based on Human-Computer Interaction Technology
School of Information and Communication Engineering, Dalian Nationalities University, Dalian, Liaoning, 116600, China
2026年7卷第5期页码：152-158
网络首发：2026-07-15，

纸质出版：2026-05-30
DOI：10.47297/taposatWSP2633-456930.20260705
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Yuyan Zhu. (2026). A Movable Waste Classification System Based on Human-Computer Interaction Technology. 科技理论与实践（英文版）, 7(5), 152-158.

Zhu Yuyan.A Movable Waste Classification System Based on Human-Computer Interaction Technology[J].Theory and Practice of Science and Technology,2026,07(05):152-158.
Yuyan Zhu. (2026). A Movable Waste Classification System Based on Human-Computer Interaction Technology. 科技理论与实践（英文版）, 7(5), 152-158. DOI： 10.47297/taposatWSP2633-456930.20260705.

Zhu Yuyan.A Movable Waste Classification System Based on Human-Computer Interaction Technology[J].Theory and Practice of Science and Technology,2026,07(05):152-158. DOI： 10.47297/taposatWSP2633-456930.20260705.

摘要

Abstract

This paper presents a movable waste classification system based on human-computer interaction technology. The system employs an STM32 microcontroller as the core control unit

integrated with an OV7725 camera and a MobileViT lightweight visual model for real-time waste identification. A dual-channel data fusion architecture combining pre-labeled reference data with dynamically captured images enhances recognition accuracy. The hardware includes a Mecanum-wheeled mobile chassis for omnidirectional movement and servo-controlled mechanisms for precise waste sorting. Multimodal interaction is achieved through an adaptive touchscreen

multi-dialect voice recognition

and a remote mobile application. An IoT-based platform with edge-cloud collaboration enables real-time monitoring and operational alerts. Experimental results demonstrate robust performance in classification accuracy and environmental adaptability. Key innovations include the dual-channel data fusion approach

integrated multimodal interaction

and networked intelligent management. This system offers significant improvements in automation efficiency and user engagement compared to conventional manual sorting methods.Compared with conventional manual sorting methods

this system offers substantial improvements in both automation efficiency and user engagement.

关键词

Keywords

references

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