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State-of-the-Art Sensors Technology in France 2023
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State-of-the-Art Sensors Technology in France 2023

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4548

Special Issue Editors

Dr. Frederick Mailly

E-Mail Website
Guest Editor
LIRMM, University of Montpellier, CNRS, 34000 Montpellier, France
Interests: MEMS; sensors; analog front end; analog-to-digital conversion; data fusion
Special Issues, Collections and Topics in MDPI journals
Dr. Emile Martincic

E-Mail Website
Guest Editor
Centre de Nanosciences et de Nanotechnologies, Universite Paris-Saclay, 91190 Saint-Aubin, France
Interests: flexible sensors; capacitive force sensors; polymers; PDMS; MEMS; lab-on-chip; micro/nanofabrication
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Pascal Nouet

E-Mail Website
Guest Editor
LIRMM, University of Montpellier, CNRS, 34000 Montpellier, France
Interests: MEMS; sensors; analog front end; analog design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to publish papers from French researchers or researchers from French laboratories in the field of sensors and MEMS. Original research and review papers are welcome. Topics of interest include, but are not limited to:

  • New sensing principles, MEMS/NEMS, components, and devices;
  • Sensor technology, packaging, advanced materials, etc.;
  • Characterization, reliability, failure analysis, fault modeling, testing, etc.;
  • Sensor modelling, design tools and methods, FEM simulation, multi-physics simulation, model order reduction, high-level modelling, co-simulation with electronics, etc.;
  • Electronic conditioning, signal processing, communication, data fusion, smart sensors, self-test, self-calibration, error correction, etc.;
  • Sensor arrays, sensor networks, multi-sensor systems;
  • Sensor applications: physical sensors, chemical sensors, RF MEMS, MOEMS, energy harvesting, biosensors, lab on chip, etc.
Dr. Frederick Mailly
Dr. Emile Martincic
Prof. Dr. Pascal Nouet
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.

Published Papers (2 papers)

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Research

18 pages, 1023 KiB  
Article
Convolutional Neural Network Bootstrapped by Dynamic Segmentation and Stigmergy-Based Encoding for Real-Time Human Activity Recognition in Smart Homes
by Houda Najeh, Christophe Lohr and Benoit Leduc
Sensors 2023, 23(4), 1969; https://doi.org/10.3390/s23041969 - 9 Feb 2023
Cited by 4 | Viewed by 1632
Abstract
Recently, deep learning (DL) approaches have been extensively employed to recognize human activities in smart buildings, which greatly broaden the scope of applications in this field. Convolutional neural networks (CNN), well known for feature extraction and activity classification, have been applied for estimating [...] Read more.
Recently, deep learning (DL) approaches have been extensively employed to recognize human activities in smart buildings, which greatly broaden the scope of applications in this field. Convolutional neural networks (CNN), well known for feature extraction and activity classification, have been applied for estimating human activities. However, most CNN-based techniques usually focus on divided sequences associated to activities, since many real-world employments require information about human activities in real time. In this work, an online human activity recognition (HAR) framework on streaming sensor is proposed. The methodology incorporates real-time dynamic segmentation, stigmergy-based encoding, and classification with a CNN2D. Dynamic segmentation decides if two succeeding events belong to the same activity segment or not. Then, because a CNN2D requires a multi-dimensional format in input, stigmergic track encoding is adopted to build encoded features in a multi-dimensional format. It adopts the directed weighted network (DWN) that takes into account the human spatio-temporal tracks with a requirement of overlapping activities. It represents a matrix that describes an activity segment. Once the DWN for each activity segment is determined, a CNN2D with a DWN in input is adopted to classify activities. The proposed approach is applied to a real case study: the “Aruba” dataset from the CASAS database. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in France 2023)
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13 pages, 919 KiB  
Article
Differential Sensing with Replicated Plasmonic Gratings Interrogated in the Optical Switch Configuration
by Emilie Laffont, Nicolas Crespo-Monteiro, Arnaud Valour, Pierre Berini and Yves Jourlin
Sensors 2023, 23(3), 1188; https://doi.org/10.3390/s23031188 - 20 Jan 2023
Cited by 6 | Viewed by 2183
Abstract
A new plasmonic configuration is proposed for application in a sensor and demonstrated for the detection of variations in the bulk refractive index of solutions. The configuration consists of monitoring two diffracted orders resulting from the interaction of a TM-polarized optical beam incident [...] Read more.
A new plasmonic configuration is proposed for application in a sensor and demonstrated for the detection of variations in the bulk refractive index of solutions. The configuration consists of monitoring two diffracted orders resulting from the interaction of a TM-polarized optical beam incident on a grating coupler, operating based on an effect termed the “optical switch”. The two monitored diffracted orders enable differential measurements which cancel the drift and perturbations common to both, leading to an improved detection limit, as demonstrated experimentally. The measured switch pattern associated with the grating coupler is in good agreement with theory. Bulk sensing is demonstrated under intensity interrogation via the sequential injection of solutions comprised of glycerol in water into a fluidic cell. A limit of detection of about 10−6 RIU was achieved. The optical switch configuration is easy to implement and is cost-effective, yielding a highly promising approach for the sensing and the real-time detection of biological species. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in France 2023)
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