Abstract
The consumer electronics (CE) industry has greatly benefited from cutting-edge technology such as the Internet of Things (IoT), artificial intelligence (AI), big data analytics, and edge computing (EC). These new emerging technologies have transformed traditional consumer systems for healthcare into smart, cost-effective, user-friendly, and sustainable consumer healthcare services. However, in such heterogeneous healthcare networks, smart devices generate large amounts of data. As a result, protecting CE and ensuring privacy preservation in healthcare systems remains an ongoing challenge. In this article, we explore the role of edge intelligence in protecting consumer electronics for healthcare services. We develop a lightweight and robust detection model using knowledge distillation-based federated learning to safeguard edge devices and ensure the privacy-preserving of consumer technology for healthcare services close to the data source. In addition, explainable AI for federated edge intelligence is used to comprehend and trust the prediction result in consumer technology. Finally, challenges, limitations, and future research are discussed.
| Original language | English |
|---|---|
| Number of pages | 9 |
| Specialist publication | IEEE Consumer Electronics Magazine |
| Publisher | Institute of Electrical and Electronics Engineers |
| DOIs | |
| Publication status | E-pub ahead of print - 2 Jan 2025 |
Keywords
- Medical services
- Security
- Data models
- Privacy
- Image edge detection
- Computational modeling
- Artificial intelligence
- Consumer electronics
- Cyberattack
- Cloud computing