Journal of Applied Science and Engineering

Published by Tamkang University Press

ESCI jase impact factor scopus logo open access rate of Scopus journal

Distributed Multimodal Data Fusion and Privacy Protection Strategies for Smart Healing Spaces: Towards Facility Operation and Maintenance Support

 2026

 Volume 35

Mo Wang, Fei Li

Jilin Animation Institute, Changchun Jilin, 130000, China

Received: July 22, 2026
Accepted: August 16, 2026
Publication Date: September 06, 2026

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Privacy-preserving federated multimodal fusion process

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Smart healing spaces rely on continuous environmental, physiological, behavioral, and feedback data to keep therapeutic facilities operating reliably and support timely maintenance decisions. Existing approaches suffer from weak multimodal fusion, poor edge coordination, and heavy communication overhead from centralized raw-data upload. This study proposes a privacy-preserving federated multimodal fusion framework for scalable, low-latency smart healing space monitoring and decision support, with facility operation and maintenance as a prospective extension: edge nodes preprocess environmental, physiological, behavioral, and feedback data, extract modality-specific latent representations, and fuse them via mask-aware temporal attention into a unified status representation for healing-state recognition and, prospectively, equipment assessment and maintenance scheduling; local updates are clipped, DP-perturbed, and securely aggregated into a reliability-weighted global model. Results show 93.2% accuracy and 92.9% F1 in healing-state recognition (5.1/4.5 points above prior methods), 88.2% F1 under severe non-IID conditions, 38.9% lower communication overhead versus FedAvg, and membership-inference attack success reduced from 71.8% to 38.7%. These results validate healing-state recognition and the communication-latency-privacy trade-offs; facility-maintenance tasks such as sensor-fault diagnosis are an architectural extension, not separately benchmarked here.

Keywords: smart healing space, facility operation and maintenance, distributed multimodal data fusion, federated learning, privacy protection, and edge-cloud collaboration.

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