Low-Power AI Embedded Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (15 October 2023) | Viewed by 586

Special Issue Editor


E-Mail Website
Guest Editor
Computer Science Department, IT University of Copenhagen, 2300 Copenhagen, Denmark
Interests: embedded-systems; machine learning; hardware acceleration; wsn; iot

Special Issue Information

Dear Colleagues,

The development of powerful microcontrollers in robust embedded boards with cameras, sensors, and microphones poses a large challenge for various industries, as these electronic devices collect a large amount of data in different forms and process the data in servers that are exposed to malicious users who can hear the communication channels and access sensitive information. Furthermore, sending data to servers without energy-saving filters is expensive. In this scenario, decentralized computational architectures provide new techniques that, with machine learning models, might remain close to the user by keeping relevant information on the device and exchanging models instead of data.

This Special Issue calls for high-quality papers regarding machine learning algorithms and applications in IoT environments or embedded systems. Topics include, but are not limited to, the following:

  • Smart sensors;
  • Transfer learning applications;
  • Embedded systems design;
  • Power consumption analysis;
  • Outlier detection;
  • Keyword spotting;
  • Reinforcement learning in robots;
  • IoT monitoring systems;
  • Time series applications with sensors;
  • Fault diagnosis and localization;
  • Intelligent systems;
  • Classification images.

Dr. Paul D. Rosero-Montalvo
Guest Editor

Manuscript Submission Information

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Keywords

  • embedded systems
  • machine learning
  • hardware design
  • low-power design
  • IoT

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Published Papers

There is no accepted submissions to this special issue at this moment.
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