Editorial
An OpenHarmony-Based AI-Driven Edge Intelligence Framework for Manufacturing Disruption Monitoring and Resilient Response
@ARTICLE{10.4108/eetsis.13806, author={Boqiang Zhang and Yuxin Zhuo and Zhiwei Chen and Zhibin Xian and Chengming Huang and Jiamin Chen and Zonghui Huang and Weiting He}, title={An OpenHarmony-Based AI-Driven Edge Intelligence Framework for Manufacturing Disruption Monitoring and Resilient Response}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={13}, number={3}, publisher={EAI}, journal_a={SIS}, year={2026}, month={9}, keywords={Manufacturing resilience, disruption monitoring, edge intelligence, industrial patrol, OpenHarmony, SparkLink SLE}, doi={10.4108/eetsis.13806} }- Boqiang Zhang
Yuxin Zhuo
Zhiwei Chen
Zhibin Xian
Chengming Huang
Jiamin Chen
Zonghui Huang
Weiting He
Year: 2026
An OpenHarmony-Based AI-Driven Edge Intelligence Framework for Manufacturing Disruption Monitoring and Resilient Response
SIS
EAI
DOI: 10.4108/eetsis.13806
Abstract
INTRODUCTION: Delayed awareness of hazards and route restrictions can weaken manufacturing continuity. OBJECTIVES: To develop an OpenHarmony-based edge-intelligence framework for disruption monitoring and resilient patrol response. METHODS: A WS63 controller performs local sensing and PID control; SparkLink SLE transmits compact frames to a Jetson Nano running a GSConv- and MSAA-enhanced YOLOv10-N detector; an ArkTS/ArkUI application presents warnings and fallback status. RESULTS: At 3 m line of sight, SLE achieved 4.8 ± 1.2 ms RTT, 67.1% lower than matched Wi-Fi/UDP and 72.1% lower than BLE. The detector reached 83.96% mAP50, 51.74% mAP50:95, 28.3 FPS, and 3.08 FPS/W. In 500 trials, recognition accuracy was 94.0% and mean alert latency was 97.9 ± 22.6 ms. CONCLUSION: The prototype supports timely warning and continuity-oriented fallback, but evidence is limited to one robot, short-range line-of-sight tests, and traffic-sign-derived proxy events.
Copyright © 2026 Boqiang Zhang et al., licensed to EAI. This is an open access article distributed under the terms of the CC BYNC-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.