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Synergies of Soft Computing, Artificial Intelligence and Signal/Image Processing Techniques in the Advancement of Sustainable Technologies.

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A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 10430

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Special Issue Editors

Dr. Md Moinul Hossain

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Guest Editor

School of Engineering and Digital Arts, University of Kent, Canterbury, Kent, CT2 7NT, UK
Interests: Machine Learning, Process Monitoring, Instrumentation, Sensors, Image Processing and Direct Solid-Oxide Fuel Cells

Dr. Mohammad Farhan Khan

E-Mail Website
Guest Editor

Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee - 247667, India
Interests: Image/Signal Processing, Machine Learning, Artificial Intelligence, Condition Monitoring, Applied Control Theory, Soft Computing, Computational Biology, Robotic Vision System

Special Issue Information

Dear Colleagues,

Currently, the world is suffering from distress due to excessive pollution, non-affordable healthcare, climatic modifications, depletion of non-renewable resources, non-green manufacturing, etc. Over recent decades, researchers have inclined more towards the route of sustainable development, which is one of the best ways of intercepting the growth of these global issues. The literature has explicitly asserted some of the more well-known engineering techniques that play a vital role in enabling positive changes, which is helpful in counteracting global issues and advancing sustainable growth.

In order to counter the uncertain and complex problems of the world, the main perspective of this Special Issue is solely aimed at investigating the synergies of engineering-based techniques that include soft computing, artificial intelligence, and signal/image processing in advancing the sustainability technologies in the broader sense in order to partially meet the goals of the 2030 agenda for sustainable development, along with others.

We welcome submissions which cover the vital role of engineering techniques in the advancement of the following areas:

Sustainable construction;
Renewable energy and green fuel;
Water and air pollution;
Climate predictions and control;
Sustainable healthcare;
Sustainable manufacturing .

Dr. MD Moinul Hossain
Dr. Mohammad Farhan Khan
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. Sustainability 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 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

sustainability
soft computing
artificial intelligence
signal/image processing
energy
healthcare
manufacturing
fuel
environment

Published Papers (3 papers)

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Research

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13 pages, 3211 KiB

Open AccessArticle

Performance Improvement of Thermoelectric Air Cooler System by Using Variable-Pulse Current for Building Applications

by Kashif Irshad

Sustainability 2021, 13(17), 9682; https://0-doi-org.brum.beds.ac.uk/10.3390/su13179682 - 28 Aug 2021

Cited by 6 | Viewed by 3571

Abstract

The thermoelectric air conditioning system (TE-AC) is a small, noiseless alternative to standard vapor compression refrigeration (VCR) systems. The cooling characteristics of a TE-AC system operating under two conditions, i.e., steady current and current pulses, are investigated in this study. This system consists of three thermoelectric modules, a heat sink, and an air circulation fan. The result shows that maximum temperature reduction in cooling side of TE-AC system was achieved at 6 A input current under steady state operation. The optimum performance of the TE-AC system under steady state operation depends upon the combined effect of the cooling load, Joule, Fourier, and Peltier heat. In TE-AC pulse operation, both current width and cooling load applied on the cold side of the thermoelectric module (TEMs) play an important role in achieving optimum cooling performance of the system. When normal input current operation (i.e., no current pulse) was compared to pulse-operated TE-AC system operation, it was found that pulse operation provides an additional average temperature reduction of 3–4 °C on the cold side of TEMs. Although on the hot side, it maintains a temperature in the range of 18 °C to 24 °C to reduce overshoot heat flux. The duration of operation is also important in determining pulse width and pulse amplitude. Minimum and overshoot peak temperature rises during each cycle for longer run operation. In the TE-AC system, the accumulated Joule heat during a current pulse frequently causes a temperature overshoot, which lasts much longer. As a result, the next current pulse was not released until the temperature of TE was restored to its initial value. Full article

(This article belongs to the Special Issue Synergies of Soft Computing, Artificial Intelligence and Signal/Image Processing Techniques in the Advancement of Sustainable Technologies.)

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18 pages, 5127 KiB

Open AccessArticle

An IoT-Based Thermoelectric Air Management Framework for Smart Building Applications: A Case Study for Tropical Climate

by Kashif Irshad, Abdulmohsen Almalawi, Asif Irshad Khan, Md Mottahir Alam, Md. Hasan Zahir and Amjad Ali

Sustainability 2020, 12(4), 1564; https://0-doi-org.brum.beds.ac.uk/10.3390/su12041564 - 19 Feb 2020

Cited by 9 | Viewed by 3793

Abstract

This study investigates the performance of the thermoelectric air conditioning (TE-AC) system smartly controlled by the Internet of Things (IoT)-based configuration for real tropical climatic application. Air cooling management was done through thermoelectric coolers, and an Arduino microcontroller with various sensors such as a temperature sensor, simple RF modules, and actuators was used to control the indoor climatic conditions based on outdoor conditions. The result shows that when the input power supply to the IoT-based TE-AC system is increased, the cooling capacity of the framework is also enhanced. Significant power and carbon emission reduction was observed for the IoT-based TE-AC system as compared to the TE-AC system without IoT. The IoT-incorporated system also ensures better microclimatic temperature control. Additionally, the system cooling capacity improves by 14.0%, and the coefficient of performance is increased by 46.3%. Thus, this study provides a smart solution to the two major energy harvesting issues of traditional air conditioners—an increase in energy efficiency by employing a TE-AC system and a further improvement in efficiency by using an IoT-based thermal management system. Full article

(This article belongs to the Special Issue Synergies of Soft Computing, Artificial Intelligence and Signal/Image Processing Techniques in the Advancement of Sustainable Technologies.)

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Review

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26 pages, 9356 KiB

Open AccessReview

Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions—A Review

by Amjad Ali, Kashif Irshad, Mohammad Farhan Khan, Md Moinul Hossain, Ibrahim N. A. Al-Duais and Muhammad Zeeshan Malik

Sustainability 2021, 13(19), 10575; https://0-doi-org.brum.beds.ac.uk/10.3390/su131910575 - 23 Sep 2021

Cited by 10 | Viewed by 2262

Abstract

Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system’s overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015–2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions. Full article

(This article belongs to the Special Issue Synergies of Soft Computing, Artificial Intelligence and Signal/Image Processing Techniques in the Advancement of Sustainable Technologies.)

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