Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.9
Journals
Sensors
Special Issues
Smart Sensors and Devices in Artificial Intelligence II
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Smart Sensors and Devices in Artificial Intelligence II

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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 7171

Special Issue Editors

Prof. Dr. Dan Zhang

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J, Canada
Interests: robotics and mechatronics; high-performance parallel robotic machine development; sustainable/green manufacturing systems; micro/nanomanipulation and MEMS devices (sensors); micro mobile robots and control of multi-robot cooperation; intelligent servo control system for the MEMS-based high-performance micro-robot; web-based remote manipulation; rehabilitation robot and rescue robot
Prof. Dr. Xuechao Duan

E-Mail Website
Guest Editor
Institute on Mechatronics, Xidian University, 710071, No.2 Taibai Rd, Xi’an, China
Interests: parallel robots; mechatronics; intelligent control; design optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors are eyes or/and ears of an intelligent system, such as UAV, AGV and robots. With the development of material, signal processing and multidisciplinary interactions, more and more smart sensors are proposed and fabricated under increasing demands for homes, industry and military fields. Networks of sensors will be able to enhance the ability to obtain huge amounts of information (big data) and improve precision, which also mirrors the developmental tendency of modern sensors. Moreover, artificial intelligence is a novel impetus for sensors and networks, which gets sensors to learn and think and feed more efficient results back.

This Special Issue welcomes new research results from academia and industry, on the subject of “Smart Sensors and Networks”, especially sensing technologies utilizing Artificial Intelligence. The Special Issue topics include, but are not limited to:

  • smart sensors
  • biosensors
  • sensor network
  • sensor data fusion
  • artificial intelligence
  • deep learning
  • mechatronics devices for sensors
  • applications of sensors for robotics and mechatronics devices

The Special Issue also welcome excellent extended papers invited from the 2018 2nd International Conference on Artificial Intelligence Applications and Technologies (AIAAT 2018) and 2019 3rd International Conference on Artificial Intelligence Applications and Technologies (AIAAT 2019).

Prof. Dr. Dan Zhang
Prof. Dr. Xuechao Duan
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 sensors
  • biosensor
  • sensor network
  • sensor data fusion
  • artificial intelligence
  • deep learning
  • robotics
  • mechatronics devices

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 9712 KiB  
Article
Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors
by Tsige Tadesse Alemayoh, Masaaki Shintani, Jae Hoon Lee and Shingo Okamoto
Sensors 2022, 22(20), 7840; https://doi.org/10.3390/s22207840 - 15 Oct 2022
Cited by 10 | Viewed by 3893
Abstract
Digitizing handwriting is mostly performed using either image-based methods, such as optical character recognition, or utilizing two or more devices, such as a special stylus and a smart pad. The high-cost nature of this approach necessitates a cheaper and standalone smart pen. Therefore, [...] Read more.
Digitizing handwriting is mostly performed using either image-based methods, such as optical character recognition, or utilizing two or more devices, such as a special stylus and a smart pad. The high-cost nature of this approach necessitates a cheaper and standalone smart pen. Therefore, in this paper, a deep-learning-based compact smart digital pen that recognizes 36 alphanumeric characters was developed. Unlike common methods, which employ only inertial data, handwriting recognition is achieved from hand motion data captured using an inertial force sensor. The developed prototype smart pen comprises an ordinary ballpoint ink chamber, three force sensors, a six-channel inertial sensor, a microcomputer, and a plastic barrel structure. Handwritten data of the characters were recorded from six volunteers. After the data was properly trimmed and restructured, it was used to train four neural networks using deep-learning methods. These included Vision transformer (ViT), DNN (deep neural network), CNN (convolutional neural network), and LSTM (long short-term memory). The ViT network outperformed the others to achieve a validation accuracy of 99.05%. The trained model was further validated in real-time where it showed promising performance. These results will be used as a foundation to extend this investigation to include more characters and subjects. Full article
(This article belongs to the Special Issue Smart Sensors and Devices in Artificial Intelligence II)
►▼ Show Figures

Figure 1

36 pages, 4574 KiB  
Article
Quality Models for Artificial Intelligence Systems: Characteristic-Based Approach, Development and Application
by Vyacheslav Kharchenko, Herman Fesenko and Oleg Illiashenko
Sensors 2022, 22(13), 4865; https://doi.org/10.3390/s22134865 - 27 Jun 2022
Cited by 9 | Viewed by 2762
Abstract
The factors complicating the specification of requirements for artificial intelligence systems (AIS) and their verification for the AIS creation and modernization are analyzed. The harmonization of definitions and building of a hierarchy of AIS characteristics for regulation of the development of techniques and [...] Read more.
The factors complicating the specification of requirements for artificial intelligence systems (AIS) and their verification for the AIS creation and modernization are analyzed. The harmonization of definitions and building of a hierarchy of AIS characteristics for regulation of the development of techniques and tools for standardization, as well as evaluation and provision of requirements during the creation and implementation of AIS, is extremely important. The study aims to develop and demonstrate the use of quality models for artificial intelligence (AI), AI platform (AIP), and AIS based on the definition and ordering of characteristics. The principles of AI quality model development and its sequence are substantiated. Approaches to formulating definitions of AIS characteristics, methods of representation of dependencies, and hierarchies of characteristics are given. The definitions and harmonization options of hierarchical relations between 46 characteristics of AI and AIP are suggested. The quality models of AI, AIP, and AIS presented in analytical, tabular, and graph forms, are described. The so-called basic models with reduced sets of the most important characteristics are presented. Examples of AIS quality models for UAV video navigation systems and decision support systems for diagnosing diseases are described. Full article
(This article belongs to the Special Issue Smart Sensors and Devices in Artificial Intelligence II)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop