Secure and decentralized hybrid multi-face recognition for IoT applications
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Author (Corporation)
Publication date
2025
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Collections
Type
01A - Journal article
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Parent work
Sensors
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DOI of the original publication
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Series number
Volume
25
Issue / Number
18
Pages / Duration
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Publisher / Publishing institution
MDPI
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Abstract
The proliferation of smart environments and Internet of Things (IoT) applications has intensified the demand for efficient, privacy-preserving multi-face recognition systems. Conventional centralized systems suffer from latency, scalability, and security vulnerabilities. This paper presents a practical hybrid multi-face recognition framework designed for decentralized IoT deployments. Our approach leverages a pre-trained Convolutional Neural Network (VGG16) for robust feature extraction and a Support Vector Machine (SVM) for lightweight classification, enabling real-time recognition on resource-constrained devices such as IoT cameras and Raspberry Pi boards. The purpose of this work is to demonstrate the feasibility and effectiveness of a lightweight hybrid system for decentralized multi-face recognition, specifically tailored to the constraints and requirements of IoT applications. The system is validated on a custom dataset of 20 subjects collected under varied lighting conditions and facial expressions, achieving an average accuracy exceeding 95% while simultaneously recognizing multiple faces. Experimental results demonstrate the system’s potential for real-world applications in surveillance, access control, and smart home environments. The proposed architecture minimizes computational load, reduces dependency on centralized servers, and enhances privacy, offering a promising step toward scalable edge AI solutions.
Keywords
Internet of Things, convolutional neural networks, decentralization, edge AI, hybrid model, multi face-recognition, security, sensors
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ISBN
ISSN
1424-8220
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Gold
License
Citation
Abdullahu, E., Wache, H., & Piangerelli, M. (2025). Secure and decentralized hybrid multi-face recognition for IoT applications. Sensors, 25(18). https://doi.org/10.3390/s25185880