Smart Devices

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 4375

Special Issue Editor


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Guest Editor
Dept. of Electronics and Computers, Transilvania University of Braşov, 500036 Braşov, Romania
Interests: cognitive radio; broadcasting technologies; IoT and Social IoT; multisensorial media
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Special Issue Information

Dear Colleagues,

In the current context of advancements in communication technologies, computation power, and device miniaturization, smart devices are becoming a reality in our everyday life, e.g., smart watches, wristbands, intelligent sensors and actuators, smart meters, smart lighting systems, smart TVs, and even smart fridges, everything is getting smarter. The reality of the Internet of Things (IoT ) paradigm and its rapid evolution in the last few years has pushed the focus onto smart devices even more, making them a natural continuation of the current IoT technologies in various application fields. Nevertheless, there are many issues that still need to be addressed from a scientific and an applicative point of view in order to ensure the smooth development of this field and to address potential scalability problems. For example, the standardization needs for smart devices, their interoperability, search and discovery methods, and communication protocols are only a few of the issues that are still wide open. Furthermore, with the advent of novel power management methods and new battery techniques, smart devices are becoming increasingly more mobile, and as such, new problems have arisen in terms of the security and privacy of these devices. Last but not least, in light of recent events related to the virus pandemic, a new application field has arisen in using smart devices to enhance the control of the current situation and prevent similar outbreaks in the future.

This Special Issue aims to highlight the latest research results and the advances of smart devices. You are therefore invited to submit original papers presenting significant advances with respect to the state of the art in the following topics, including, but not limited to:

  • Power consumption and power optimization for smart devices;
  • Communication issues for smart devices;
  • IoT, M2M, and smart devices convergence;
  • Standardization issues for smart devices;
  • Security and privacy issues for smart devices;
  • Search, discovery, and collaboration among smart devices;
  • Smart environments;
  • Smart devices for vehicular applications;
  • Smart devices for mobility management;
  • Smart devices in the smart cities context;
  • Smart devices for medical assistance and healthcare applications;
  • Scalability issues for smart devices.

Dr. Vlad Popescu
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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 devices
  • cooperation
  • convergence
  • aggregation
  • smart environments

Published Papers (1 paper)

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Research

33 pages, 13962 KiB  
Article
Artificial Intelligence for the Prediction of Exhaust Back Pressure Effect on the Performance of Diesel Engines
by Vlad Fernoaga, Venetia Sandu and Titus Balan
Appl. Sci. 2020, 10(20), 7370; https://0-doi-org.brum.beds.ac.uk/10.3390/app10207370 - 21 Oct 2020
Cited by 8 | Viewed by 3777
Abstract
The actual trade-off among engine emissions and performance requires detailed investigations into exhaust system configurations. Correlations among engine data acquired by sensors are susceptible to artificial intelligence (AI)-driven performance assessment. The influence of exhaust back pressure (EBP) on engine performance, mainly on effective [...] Read more.
The actual trade-off among engine emissions and performance requires detailed investigations into exhaust system configurations. Correlations among engine data acquired by sensors are susceptible to artificial intelligence (AI)-driven performance assessment. The influence of exhaust back pressure (EBP) on engine performance, mainly on effective power, was investigated on a turbocharged diesel engine tested on an instrumented dynamometric test-bench. The EBP was externally applied at steady state operation modes defined by speed and load. A complete dataset was collected to supply the statistical analysis and machine learning phases—the training and testing of all the AI solutions developed in order to predict the effective power. By extending the cloud-/edge-computing model with the cloud AI/edge AI paradigm, comprehensive research was conducted on the algorithms and software frameworks most suited to vehicular smart devices. A selection of artificial neural networks (ANNs) and regressors was implemented and evaluated. Two proof-of concept smart devices were built using state-of-the-art technology—one with hardware acceleration for “complete cycle” AI and the other with a compact code and size (“AI in a nut-shell”) with ANN coefficients embedded in the code and occasionally offline “statistical re-calibration”. Full article
(This article belongs to the Special Issue Smart Devices)
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