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Applications of Internet of Things and Artificial Intelligence for Smart Urban Living from a Sustainable Perspective

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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 6831

Special Issue Editors

Dr. Pg Emeroylariffion Abas

E-Mail Website
Guest Editor
Faculty of Integrated Technologies, Universiti Brunei Darussalam, Gadong BE1410, Brunei
Interests: artificial intelligence; energy; signal processing; data analytics; sustainable living; photonics
Prof. Dr. T. M. Indra Mahlia

grade E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
Interests: sustainable energy; energy and fuels; renewable energy; techno-economic analysis and life-cycle cost analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Making cities and human settlements inclusive, safe, resilient and sustainable is one of the 17 Sustainable Development Goals (SDGs) put forward by the United Nations (UN) to create a better future by 2030. This stems from the realization of the importance of cities as centers for social, human and economic development, as well as the realization that the growth of these urban developments needs to be sustainable for future generations. Included under this goal are multifaceted and interconnected issues related to sustainable urban development.

At the same time, we are seeing an increase in the usage of artificial intelligence (AI) in various applications, with AI set to shape the future across every industry. The availability of big data from multiple sensors and other sources, affordable connectivity, and the increasing processing power of the Internet of Things (IoT) have facilitated the fast and accurate interpretation of sensor data, which can be used to provide valuable and timely feedback to the IoT ecosystem. The popularity of AI is set to increase even further with the declining price of semiconductors, making processing power faster while maintaining affordability.

The purpose of this Special Issue is to gather original contributions and review articles focusing on the applications of artificial intelligence, including machine learning and deep learning, in the process of developing sustainable and smart urban living. This includes the use of AI in improving urban planning, transport systems, energy systems, water supply systems, sanitation systems and waste management systems. Also relevant are the applications of AI in reducing and mitigating risks from different disasters, including natural disasters such as flooding, earthquakes and strong winds. As social and educational developments in the population play an important role in urban living, research efforts to improve education, general development, capacity building and access to information using AI are also welcome. Subsequently, this Special Issue is intended to pave the way and focus on future works in the area.

Dr. Pg Emeroylariffion Abas
Prof. Dr. T M Indra Mahlia
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

  • sustainable living
  • artificial intelligence
  • machine learning
  • deep learning
  • sustainability
  • smart city
  • smart urban living
  • Internet of Things
  • IoT

Published Papers (2 papers)

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Research

17 pages, 2084 KiB  
Article
Identifying Smart City Leaders and Followers with Machine Learning
by Fangyao Liu, Nicole Damen, Zhengxin Chen, Yong Shi, Sihai Guan and Daji Ergu
Sustainability 2023, 15(12), 9671; https://doi.org/10.3390/su15129671 - 16 Jun 2023
Cited by 3 | Viewed by 1079
Abstract
Smart cities have been a popular topic for the city stakeholders. A smart city is the next urban lifestyle that citizens expect. Due to the hypercompetitive and globalized economy, many cities have already started or are about to start their smart city projects. [...] Read more.
Smart cities have been a popular topic for the city stakeholders. A smart city is the next urban lifestyle that citizens expect. Due to the hypercompetitive and globalized economy, many cities have already started or are about to start their smart city projects. There is no uniform benchmark to evaluate the smart cities’ performance. Several organizations use their own indicators to evaluate smart cities worldwide or nationwide. This research paper leverages fuzzy logic to label smart city leaders and followers based on various organization’s evaluation meta results and then uses machine learning techniques to identify the key characteristics of leaders and followers. Based on the training data performance, the Support Vector Machine (SVM) is used to predict who will be the next smart city leader or follower. According to the proposed prediction framework, we have successfully predicted 30 smart city leaders and 20 followers. Full article
(This article belongs to the Special Issue Applications of Internet of Things and Artificial Intelligence for Smart Urban Living from a Sustainable Perspective)
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17 pages, 8309 KiB  
Article
HVAC Control Systems for a Negative Air Pressure Isolation Room and Its Performance
by Hamdani Hamdani, Fajar Salamul Sabri, Harapan Harapan, Maimun Syukri, Razali Razali, Rudi Kurniawan, Irwansyah Irwansyah, Sarwo Edhy Sofyan, Teuku Meurah Indra Mahlia and Samsul Rizal
Sustainability 2022, 14(18), 11537; https://doi.org/10.3390/su141811537 - 14 Sep 2022
Cited by 2 | Viewed by 4255
Abstract
The controlled environment room, called an isolation room, has become a must have for medical facilities, due to the spreading of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), to isolate the high risk infected patients. To avoid the transmission of the virus through [...] Read more.
The controlled environment room, called an isolation room, has become a must have for medical facilities, due to the spreading of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), to isolate the high risk infected patients. To avoid the transmission of the virus through airborne routes, guidelines were published by the government and the association. A medical facility must comply with this document for high-risk patient treatment. A full-scale N class isolation room was built at Syiah Kuala University to investigate the performance in terms of the controller, temperature, pressure, humidity, and energy consumption. The isolation room was equipped with a proper capacity heating, ventilating, and air conditioning (HVAC) system, which consisted of an air conditioning compressor and a negative pressure generator (NPG), and its installation was ensured to fulfil the guidelines. Since the current NPG was controlled manually, a computer-based control system was designed, implemented, and compared with the manual control. The results showed that the computer-based control outputs better stability of pressure and electric power. For that reason, a computer-based control was chosen in the real case. To investigate the performance of the isolation room, a 24 h experiment was carried out under different parameter setups. The results showed that improvement of the control strategy for temperature and humidity is still necessary. The energy consumption during the activation of the NPG for the recommended negative pressure was slightly different. An additional piece of equipment to absorb the heat from the exhaust air would be promising to improve the energy efficiency. Full article
(This article belongs to the Special Issue Applications of Internet of Things and Artificial Intelligence for Smart Urban Living from a Sustainable Perspective)
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