IoT-Based Smart Security Alarm Systems

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E:Engineering and Technology".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 3498

Special Issue Editor

Department of Security Management, Faculty of Security Engineering, University of Zilina, 010 26 Žilina, Slovakia
Interests: physical protection systems; alarm systems; access control; security services

Special Issue Information

Dear Colleagues,

The term “Internet of Things” (IoT) is increasingly emerging in the security sciences. New concepts of security alarm systems are emerging, which participate in the creation of the so-called smart home. These systems offer many possibilities to integrate the Internet into alarm system components or to complement and connect existing solutions. Compliance with technical standards focused on alarm systems will be an interesting challenge. Without meeting the parameters set therein, it is not possible to talk about professional alarm systems, and dealing with a possible insurance event in connection with a security incident can be complicated. All components of the alarm system shall, according to the standard, meet the appropriate degree of security. Despite minor complications, the market opens up a room for the use of IoT alarm devices in homes and the implementation of IoT functions into professional alarm systems. The majority of them are now programmed via an Internet interface and include the ability to connect the alarm system to a mobile phone application. This includes cybersecurity solutions that should address the risks associated with data sharing and network security where devices can interoperate.

Special Issue seeks to showcase research papers, short communications, and review articles that focus on development in IoT security alarm systems and their use in protection.

Dr. Andrej Velas
Guest Editor

Manuscript Submission Information

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Keywords

  • security alarm systems
  • IoT
  • burglar alarm
  • access control
  • alarm transmission
  • smart home security

Published Papers (1 paper)

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Research

24 pages, 12529 KiB  
Article
Explainable AI for Bearing Fault Prognosis Using Deep Learning Techniques
by Deva Chaitanya Sanakkayala, Vijayakumar Varadarajan, Namya Kumar, Karan, Girija Soni, Pooja Kamat, Satish Kumar, Shruti Patil and Ketan Kotecha
Micromachines 2022, 13(9), 1471; https://doi.org/10.3390/mi13091471 - 05 Sep 2022
Cited by 13 | Viewed by 2700
Abstract
Predicting bearing failures is a vital component of machine health monitoring since bearings are essential parts of rotary machines, particularly large motor machines. In addition, determining the degree of bearing degeneration will aid firms in scheduling maintenance. Maintenance engineers may be gradually supplanted [...] Read more.
Predicting bearing failures is a vital component of machine health monitoring since bearings are essential parts of rotary machines, particularly large motor machines. In addition, determining the degree of bearing degeneration will aid firms in scheduling maintenance. Maintenance engineers may be gradually supplanted by an automated detection technique in identifying motor issues as improvements in the extraction of useful information from vibration signals are made. State-of-the-art deep learning approaches, in particular, have made a considerable contribution to automatic defect identification. Under variable shaft speed, this research presents a novel approach for identifying bearing defects and their amount of degradation. In the proposed approach, vibration signals are represented by spectrograms, and deep learning methods are applied via pre-processing with the short-time Fourier transform (STFT). A convolutional neural network (CNN), VGG16, is then used to extract features and classify health status. After this, RUL prediction is carried out with the use of regression. Explainable AI using LIME was used to identify the part of the image used by the CNN algorithm to give the output. Our proposed method was able to achieve very high accuracy and robustness for bearing faults, according to numerous experiments. Full article
(This article belongs to the Special Issue IoT-Based Smart Security Alarm Systems)
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