Special Issue "Wireless Sensor Networks on Internet of Things and Intelligent System"

A special issue of Applied System Innovation (ISSN 2571-5577).

Deadline for manuscript submissions: 31 December 2018

Special Issue Editors

Guest Editor
Prof. Subhas Mukhopadhyay

School of Engineering, MQ Centre for Smart Green Cities, Macquarie University, NSW 2109, Australia
Website | E-Mail
Phone: +61-2-9850-6510
Fax: +61-2-9850-9128
Interests: WSN; IoT; Body Area Networks; Sensor Applications; Sensor Fabrication; Mechanical Sensors; Chemical/Gas/Biological/Solid State Sensors
Guest Editor
Prof. Dr. Jih-Fu Tu

Department of Electronic Engineering, St. John's University, No. 499, Sec. 4, Tam King Road, Tamsui District, New Taipei City 25135, Taiwan
E-Mail
Interests: Discrete event systems; Internet of Things (IoT) application design; Smart Motion system design; programmable system control

Special Issue Information

Dear Colleagues,

In the coming years, the “Industry 4.0” is an important hub for mechanical, electrical and other “hidden champion” industries. No matter how, the government, companies, academies have devoted many resource and much effort to raising the industrial. The Internet of Thing (IoT) and Intelligence System are based on Wireless Sensor Networks (WSN) to attach and had become one of the well-known scientific events worldwide in industry. We invite the submission of papers related to various aspects of Wireless Sensor Networks to apply in Intelligence Design and System of industries.

The main topics of interest include, but are not limited to:

  • Theories or application of Wireless Sensor Networks (WSN)
  • Theories or application of Internet-of-Things (IoT)
  • Intelligence Electronic Circuits and Systems Design
  • Design, Simulation, and Applications of Intelligence Electronic Circuits
  • Saving Energy and Electrical Engineering Methods
  • Intelligence Theories, System, and Circuits Design
  • Intelligence Circuit and System Design Tools
  • Big Data Communication and Databased Applied on IoT
  • Others related to Wireless Sensor Networks or Intelligence Design and System

Prof. Dr. Subhas Chandra Mukhopadhyay
Prof. Dr. Jih-Fu Tu
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 papers will be 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. Applied System Innovation is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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

Open AccessArticle Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring and Smart Home Security for Wellness Protocol
Appl. Syst. Innov. 2018, 1(4), 42; https://doi.org/10.3390/asi1040042
Received: 19 September 2018 / Revised: 15 October 2018 / Accepted: 16 October 2018 / Published: 23 October 2018
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Abstract
The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an ongoing theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research
[...] Read more.
The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an ongoing theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research gaps. The problems found with existing systems were that they can only identify the intruder after the theft, or cannot distinguish between human and non-human objects. Wireless Sensors Networks (WSNs) combined with the use of Internet of Things (IoT) and Cognitive Internet of Things are expanding smart home concepts and solutions, and their applications. The present research proposes a novel smart home anti-theft system that can detect an intruder, even if they have partially/fully hidden their face using clothing, leather, fiber, or plastic materials. The proposed system can also detect an intruder in the dark using a CCTV camera without night vision capability. The fundamental idea was to design a cost-effective and efficient system for an individual to be able to detect any kind of theft in real-time and provide instant notification of the theft to the house owner. The system also promises to implement home security with large video data handling in real-time. The investigation results validate the success of the proposed system. The system accuracy has been enhanced to 97.01%, 84.13, 78.19%, and 66.5%, in scenarios where a detected intruder had not hidden his/her face, hidden his/her face partially, fully, and was detected in the dark from 85%, 64.13%, 56.70%, and 44.01%. Full article
(This article belongs to the Special Issue Wireless Sensor Networks on Internet of Things and Intelligent System)
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Open AccessArticle Developing a Decision Support System (DSS) for a Dental Manufacturing Production Line Based on Data Mining
Appl. Syst. Innov. 2018, 1(2), 17; https://doi.org/10.3390/asi1020017
Received: 7 April 2018 / Revised: 27 May 2018 / Accepted: 27 May 2018 / Published: 30 May 2018
PDF Full-text (5067 KB) | HTML Full-text | XML Full-text
Abstract
In this study, an Industry 4.0 framework-based decision support system (DSS) was developed using a combination of wireless network and RFID identification technology to manage a production line in a traditional dental manufacturing lab. The motivation was to prevent mistakes from manual recording,
[...] Read more.
In this study, an Industry 4.0 framework-based decision support system (DSS) was developed using a combination of wireless network and RFID identification technology to manage a production line in a traditional dental manufacturing lab. The motivation was to prevent mistakes from manual recording, to remotely monitor the working hours of employees in manufacturing processes via internet, and to evaluate the rationality of the employee’s working hours. In the DSS, four network nodes were established to track four important manufacturing processes of digital dentistry. In each of these processes, the time spent by the dental technician was recorded by scanning their ID cards. All information was simultaneously uploaded to a databank in the cloud and analyzed by the computer software MATLAB. These programs evaluated the rationality of employees’ working hours in each of the monitored processes, which can help managers to follow up or improve the process efficiency. Full article
(This article belongs to the Special Issue Wireless Sensor Networks on Internet of Things and Intelligent System)
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