Smart Edge Devices: Design and Applications

Dear Colleagues,

Edge devices are a critical part of the expanding Internet of Things (IoT) ecosystem. They play a key role in bringing computational power closer to the data source, allowing for faster decision-making, better privacy control, and reduced reliance on centralized cloud computing. Deep learning is increasingly being deployed for edge devices to enable real-time decision-making and intelligent processing directly at the source of data, converting them into smart edge devices. These devices can perform complex tasks such as image recognition, speech processing, and predictive analytics locally without relying heavily on cloud-based computing. This has led to a variety of applications across industries, including healthcare, automotive, manufacturing, and more.

The present Topic aims to publish new knowledge on smart edge devices by bringing together works on the design and applications of these systems. Topics of interest include, but are not limited to, the following:

• Design of smart edge devices:
  • Microprocessors for edge computing;
  • Sensors for data collection;
  • Protocols and modules for connectivity of edge devices;
  • Local storage architectures;
  • Power management systems;
  • Machine and deep learning models for edge computing;
  • Embedded computing architectures;
  • Custom design of accelerators for edge computing;
  • New high-performance devices for embedded deep learning.
• Applications of smart edge devices:
  • Smart healthcare;
  • Industrial automation;
  • Autonomous vehicles;
  • Smart cities;
  • Edge devices in agriculture;
  • Retail and consumer electronics;
  • Energy management;
  • Space data analysis.

Dr. Mário Véstias
Dr. Rui Policarpo Duarte
Topic Editors