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Integrated Circuit and System Design for Smart Sensors
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Integrated Circuit and System Design for Smart Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (25 April 2023) | Viewed by 1866

Special Issue Editors

Dr. Paul P. Sotiriadis

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: design, optimization, and mathematical modeling of analog; mixed-signal, RF and microwave integrated and discrete circuits; sensors and instrumentation architectures; biomedical instrumentation; interconnect networks and advanced frequency synthesis
Dr. Christos Dimas

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: design; biomedical instrumentation; electrical impedance tomography; inverse problems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Integrated circuits and systems are unambiguous parts of modern sensors and, in some cases, co-integrated with them on the same silicon die. The advancement of integration technology allows us to implement sophisticated signal conditioning and processing techniques around the actual sensing element in both the analog and digital domains. This has opened the way for intelligent and Internet of Things sensors of miniature size, with signal processing and feature extraction (Edge AI) as well as wireless communication capabilities. Smart sensing is essential in many modern devices and applications, such as in cellphones, autonomous cars and vessels, household appliances, health monitoring, industrial equipment control systems, environmental probing and field detection, and many others.

The Special Issue “Integrated Circuit and System Design for Smart Sensors” focuses on the development of advanced sensor front-end integrated circuit architectures and implementations, aiming towards a wide variety of applications. Both original research and survey (review) papers are welcomed.

Topics of interest and applications for this Special Issue include, but are not limited to, the following:

  • Analog/digital integrated circuits for smart sensors.
  • Analog data signal conditioning circuits.
  • In-and-near memory processing for edge computing.
  • Ultra-low power, sub-threshold sensor’s circuits.
  • Biologically inspired sensor circuits and systems.
  • Low-cost wearable sensor circuits and systems.
  • Flexible integrated circuits and systems for sensors.
  • Integrated sensors for predictive maintenance.
  • IoT sensor circuits and systems.
  • Intelligent (AI) sensor circuits and systems.
  • Radar/RF/acoustic sensor circuits and systems.
  • Integrated sensors for medical and automotive applications.
  • Integrated sensors for control and automation applications.

Experimental or simulation results validating the proposed architecture or system are required.

Best regards,

Dr. Paul P. Sotiriadis
Dr. Christos Dimas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart sensor
  • integrated circuit
  • analog
  • digital
  • low power
  • edge computing
  • wearable
  • bio-signals
  • flexible

Published Papers (1 paper)

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Research

20 pages, 819 KiB  
Article
A Low-Power Analog Integrated Implementation of the Support Vector Machine Algorithm with On-Chip Learning Tested on a Bearing Fault Application
by Vassilis Alimisis, Georgios Gennis, Marios Gourdouparis, Christos Dimas and Paul P. Sotiriadis
Sensors 2023, 23(8), 3978; https://doi.org/10.3390/s23083978 - 14 Apr 2023
Cited by 12 | Viewed by 1513
Abstract
A novel analog integrated implementation of a hardware-friendly support vector machine algorithm that can be a part of a classification system is presented in this work. The utilized architecture is capable of on-chip learning, making the overall circuit completely autonomous at the cost [...] Read more.
A novel analog integrated implementation of a hardware-friendly support vector machine algorithm that can be a part of a classification system is presented in this work. The utilized architecture is capable of on-chip learning, making the overall circuit completely autonomous at the cost of power and area efficiency. Nonetheless, using subthreshold region techniques and a low power supply voltage (at only 0.6 V), the overall power consumption is 72 μW. The classifier consists of two main components, the learning and the classification blocks, both of which are based on the mathematical equations of the hardware-friendly algorithm. Based on a real-world dataset, the proposed classifier achieves only 1.4% less average accuracy than a software-based implementation of the same model. Both design procedure and all post-layout simulations are conducted in the Cadence IC Suite, in a TSMC 90 nm CMOS process. Full article
(This article belongs to the Special Issue Integrated Circuit and System Design for Smart Sensors)
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