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The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 65707

Special Issue Editor

Prof. Dr. Fadi Al-Turjman

E-Mail Website
Guest Editor
Artificial Intelligence Engineering Department, Research Center for AI and IoT, AI & Robotics Institute, Near East University, North Cyprus via Mersin 10, Nicosia 99138, Turkey
Interests: IoT; AI; cloud computing; blockchain; AIoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is becoming a key enabling technology, with multiple innovations supporting the smart city paradigm. For instance, providing multi-hop collaboration among IoT sensor networks helps to reach possible services from Cloud computing facilities, and machine learning (ML) techniques are employed to adapt existing configurations. Moreover, emerging 5th and 6th generation (5G/6G) technologies can revolutionize ubiquitous computing with numerous sustainable applications built around various "smart" sensors enabled with cognition and ML techniques. ML has shown an outstanding performance in complicated tasks that require human-like intelligence and intuition. It is capable of detecting hidden structures in data and using that to make smart decisions in smart cities' critical missions. To successfully accomplish this vision, cognitive IoT solutions are needed to reshape the existing smart applications toward further sustainable services in smart city paradigms. This Special Issue brings together a broad multidisciplinary community studying cognitive architectures across science and engineering. It aims to integrate ideas, theories, models, and techniques from across different disciplines on cognitive architectures. Potential topics include but are not limited to:

  • IoT communication protocols for sustainable smart cities
  • Cognitive resource management in IoT
  • ML and intelligent IoT-based localization
  • Intelligent blockchain for sustainable cities
  • AI algorithms in the IoT era
  • Enablers for intelligent/secured IoT
  • Use cases enabled by intelligent IoT in Smart cities
  • IoT and ML in smart cities
  • ML and mobile assisted public safety and emergency IoT
  • Intelligent 5G/6G communication for sustainable cities
  • Design and evaluation of IoT test beds, prototypes, and platforms

Prof. Dr. Fadi Al-Turjman
Guest Editor

Manuscript Submission Information

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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

  • IoT
  • sustainable smart cities
  • deep learning
  • machine learning, smart apps

Published Papers (23 papers)

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15 pages, 4096 KiB  
Article
Digital Transformation to Help Carbon Neutrality and Green Sustainable Development Based on the Metaverse
by Weiran Cao, Zengjie Cai, Xu Yao and Lifeng Chen
Sustainability 2023, 15(9), 7132; https://doi.org/10.3390/su15097132 - 24 Apr 2023
Cited by 3 | Viewed by 1712
Abstract
With the development of sustainable theory, environmental and resource issues have become one of the major challenges facing human society. As an important part of social economy, enterprises are also an important source of carbon emissions and environmental pollution. With the growth of [...] Read more.
With the development of sustainable theory, environmental and resource issues have become one of the major challenges facing human society. As an important part of social economy, enterprises are also an important source of carbon emissions and environmental pollution. With the growth of the digital economy, digital technology has played an important role in improving economic efficiency. Digital transformation can not only enable enterprises to obtain and allocate resources more efficiently and reasonably, but can also provide a powerful driving force for the healthy development of the environment. This can improve the positive role and impact of enterprises on environmental development. Based on the overview of social carbon neutrality and green sustainable development goals, this paper made an in-depth study of digital transformation to help carbon neutrality and green sustainable development. In order to verify its effect, this paper took a medium-sized enterprise as the object, analyzed the growth of its economic and environmental benefits in the process of digital transformation, and compared it with the traditional development strategy. The empirical results showed that in the perspective of the Metaverse, the highest growth rate of environmental benefits of the enterprise would reach 19.6% every month in 2021. From this data, digital transformation based on the perspective of the Metaverse was more able to help carbon neutrality and green sustainable development. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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14 pages, 5456 KiB  
Article
Intrusion Detection Using Chaotic Poor and Rich Optimization with Deep Learning Model for Smart City Environment
by Fatma S. Alrayes, Mashael M. Asiri, Mashael Maashi, Ahmed S. Salama, Manar Ahmed Hamza, Sara Saadeldeen Ibrahim, Abu Sarwar Zamani and Mohamed Ibrahim Alsaid
Sustainability 2023, 15(8), 6902; https://doi.org/10.3390/su15086902 - 19 Apr 2023
Cited by 4 | Viewed by 1219
Abstract
Artificial intelligence (AI) techniques play a vital role in the evolving growth and rapid development of smart cities. To develop a smart environment, enhancements to the execution, sustainability, and security of traditional mechanisms become mandatory. Intrusion detection systems (IDS) can be considered an [...] Read more.
Artificial intelligence (AI) techniques play a vital role in the evolving growth and rapid development of smart cities. To develop a smart environment, enhancements to the execution, sustainability, and security of traditional mechanisms become mandatory. Intrusion detection systems (IDS) can be considered an effective solutions to achieve security in the smart environment. This article introduces intrusion detection using chaotic poor and rich optimization with a deep learning model (IDCPRO-DLM) for ubiquitous and smart atmospheres. The IDCPRO-DLM model follows preprocessing, feature selection, and classification stages. At the initial stage, the Z-score data normalization system is exploited to scale the input data. Additionally, the IDCPRO-DLM method designs a chaotic poor and rich optimization algorithm-based feature selection (CPROA-FS) approach for selecting feature subsets. For intrusion detection, butterfly optimization algorithm (BOA) with a deep sparse autoencoder (DSAE) is used. The simulation analysis of the IDCPRO-DLM technique is studied on the benchmark CICIDS dataset and the comparison results show the better performance of the IDCPRO-DLM algorithm over recent state-of-the-art approaches with a maximum accuracy of 98.53%. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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15 pages, 4690 KiB  
Article
Research on Acquisition Performance of FFT Algorithm for Low-Frequency Spread-Spectrum Signals Using Acoustic Sensors
by Yongzhuang Tang, Qidou Zhou, Zhiyong Xie, Wenxi Liu and Xiaojun Lü
Sustainability 2023, 15(8), 6405; https://doi.org/10.3390/su15086405 - 9 Apr 2023
Cited by 2 | Viewed by 1225
Abstract
An essential precondition for the effective use of low-frequency spread-spectrum acoustic signals is their synchronous acquisition. Due to the low bit rate that low-frequency spread-spectrum signals have, the length of the spreading spectrum code and the number of intra-chip carriers need to be [...] Read more.
An essential precondition for the effective use of low-frequency spread-spectrum acoustic signals is their synchronous acquisition. Due to the low bit rate that low-frequency spread-spectrum signals have, the length of the spreading spectrum code and the number of intra-chip carriers need to be precisely designed to balance the acquisition performance and the bit rate in low-frequency spread-spectrum signals. Furthermore, the selection of the acquisition method and sampling frequency depends on the specific application and system requirements, which will directly affect the processing speed and accuracy. Firstly, this study uses a cyclical stepping search combined with a fixed threshold and maximum correlation discriminant method to improve the FFT acquisition algorithm with a low Doppler frequency. Secondly, the effects of the spreading spectrum code parameters and sampling frequency on the acquisition performance are also investigated through simulation and experiments with acoustic sensors. The results show that both lengthening the spreading spectrum code and increasing the number of intra-chip carriers can greatly improve the acquisition performance. Increasing the sampling frequency can improve the ranging accuracy but has a very limited improvement effect on the acquisition performance. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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16 pages, 3066 KiB  
Article
Sustainable Development of Business Economy Based on Big Data Algorithm under the Background of Low-Carbon Economy
by Xuefeng Liu and Li Ma
Sustainability 2023, 15(7), 5840; https://doi.org/10.3390/su15075840 - 28 Mar 2023
Cited by 1 | Viewed by 1168
Abstract
After the low-carbon economy (LCE) was proposed, countries all over the world examined their national economic structures and found the necessity for developing a LCE. Therefore, it is necessary to vigorously develop low-carbon technologies and improve technological and policy innovation capabilities. From the [...] Read more.
After the low-carbon economy (LCE) was proposed, countries all over the world examined their national economic structures and found the necessity for developing a LCE. Therefore, it is necessary to vigorously develop low-carbon technologies and improve technological and policy innovation capabilities. From the perspective of promoting the coordinated development of the low-carbon economic system and regional sustainable development, this paper conducted an in-depth analysis of the coordinated development of the low-carbon economic system and regional environmental issues by using the relevant theories of sustainable development, low-carbon economics, and environmental economics. The index system of the low-carbon economic system and regional sustainable development was constructed, and the coupling degree model and regional coupling coordination degree model suitable for the development of the low-carbon economic system and regional sustainable development were established. On the basis of analyzing the status quo of a LCE and the environment in a coastal area, it was finally concluded that in the next five years, the value of the coupling coordination degree of the LCE and its sustainable system development would continue to approach 1 and grow steadily. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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16 pages, 2691 KiB  
Article
Framework for Building Smart Tourism Big Data Mining Model for Sustainable Development
by Ruoran Xu
Sustainability 2023, 15(6), 5162; https://doi.org/10.3390/su15065162 - 14 Mar 2023
Cited by 2 | Viewed by 2161
Abstract
How to combine big data (BD) technology with specific applications in the tourism industry to achieve sustainable development in the tourism industry is a development issue that needs to be addressed in the tourism industry today. In order to promote the development of [...] Read more.
How to combine big data (BD) technology with specific applications in the tourism industry to achieve sustainable development in the tourism industry is a development issue that needs to be addressed in the tourism industry today. In order to promote the development of smart tourism, this text constructed a BD mining model for sustainable smart tourism. In this paper, based on tourism data from 2010 to 2021, a regression model and an exponential curve model are constructed to forecast passenger traffic, and a tourism spatial dimension model is constructed to build a tourism data table, pre-process the data and construct a data mining (DM) model using a SQL Server model. The experimental part of the study conducts experimental research on cities applying smart tourism DM technology in three areas: foreign exchange earnings from the city’s tourism industry, jobs in the tourism industry and the development of tourism-related industries. The results showed that the application of smart tourism DM technology can improve the foreign exchange income (FEI) of urban tourism, increase employment in tourism and drive the development of tourism-related industries. Compared with 2010, the tourism FEI of the four cities would increase by more than 70% in 2021. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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25 pages, 24058 KiB  
Article
Big Data Application in Urban Commercial Center System Evaluation
by Xinyu Liu, Yibing Guan, Zihan Wu, Lufeng Nie and Xiang Ji
Sustainability 2023, 15(5), 4205; https://doi.org/10.3390/su15054205 - 26 Feb 2023
Cited by 1 | Viewed by 1572
Abstract
Big data has provided new opportunities, directions, and methods for research on urban commercial center systems. Based on a quantitative assessment of big data and public participation, the “big data + public feedback” evaluation model can objectively and scientifically quantify the scale and [...] Read more.
Big data has provided new opportunities, directions, and methods for research on urban commercial center systems. Based on a quantitative assessment of big data and public participation, the “big data + public feedback” evaluation model can objectively and scientifically quantify the scale and structural characteristics of urban commercial center systems. In this paper, socioeconomic and material spatial attributes were considered in the selection of four indexes, including commercial agglomeration centrality, commercial facility service level, commercial industry status, and industry attraction. Specifically, we based our selection on the big data of the point-of-interest network, housing price, and population. ArcGIS, SPSS, and other analytical tools were employed to conduct a comparative analysis, cluster analysis, spatial network analysis, and correlation analysis. Using these data, we constructed an assessment index system, which was then utilized to comprehensively evaluate the current commercial land use in Nanjing’s main urban area and measure the degree of commercialization. The commercial center system in the main urban area of Nanjing was found to be consistent with the spatial structure system of “one main core, five secondary cores, multiple district cores, three horizontal axes, and one vertical axis.” Meanwhile, a public questionnaire was used to evaluate the public’s perception of the commercialization level in Nanjing. Finally, the results obtained were used for comparison with the structure of the commercial center system of Nanjing commercial network planning. We discovered that the results of the public’s perception of the commercialization level in Nanjing were similar to those of the big data analysis, which confirmed the credibility of big data analysis results. In conclusion, the findings of this study provide a basis for developing urban commercial center-level positioning and propose a method for data-assisted planning research. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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14 pages, 2090 KiB  
Article
Smart Agriculture and Rural Revitalization and Development Based on the Internet of Things under the Background of Big Data
by Xi Ma
Sustainability 2023, 15(4), 3352; https://doi.org/10.3390/su15043352 - 11 Feb 2023
Cited by 3 | Viewed by 2432
Abstract
Smart agriculture refers to the specific performance of the smart economy in the field of agriculture; it is a form of agricultural smart economy and an important part of the smart economy. It has played a certain role in promoting rural revitalization and [...] Read more.
Smart agriculture refers to the specific performance of the smart economy in the field of agriculture; it is a form of agricultural smart economy and an important part of the smart economy. It has played a certain role in promoting rural revitalization and development. The purpose of this paper was to study the role of smart agriculture based on the Internet of Things in rural revitalization and development under the background of big data. The purpose was to use Internet of Things technology to realize smart agriculture under the background of big data, so as to promote rapid rural revitalization and development. Therefore, in this paper, a fuzzy PID algorithm and genetic algorithm were proposed. Finally, through experimental analysis, the fuzzy PID algorithm was used to carry out experiments in the laboratory. The temperature and humidity of the laboratory were measured. The average difference between the collected and actual temperature values was 0.6 °C, and the maximum difference between the collected and actual humidity values was 1.32% RH. The laboratory simulation results satisfied the performance indicators and technical requirements of the system. The system operated normally and could be directly applied to field tests. The experimental results show that the role of Internet of Things technology in the smart agricultural economy is irreplaceable, which further illustrates the positive relationship between smart agriculture based on the Internet of Things and rural revitalization and development. As one of the most mature technologies in today’s society, the Internet of Things technology combined with smart agriculture not only offers new perspectives, but also promotes the revitalization and development of rural areas, indicating a new direction for its future research. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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14 pages, 2326 KiB  
Article
Strategies for Environmental Protection and Optimization of Ecological Business Economic Growth from the Perspective of Sustainable Development
by Li Ma and Xuefeng Liu
Sustainability 2023, 15(3), 2758; https://doi.org/10.3390/su15032758 - 2 Feb 2023
Cited by 1 | Viewed by 1964
Abstract
The concept of ecological commercial economy refers to the use of ecological economics principles and system engineering methods to change production and consumption patterns within the scope of the carrying capacity of the ecosystem in order to tap into all of the available [...] Read more.
The concept of ecological commercial economy refers to the use of ecological economics principles and system engineering methods to change production and consumption patterns within the scope of the carrying capacity of the ecosystem in order to tap into all of the available resource potential. It develops some economically developed and ecologically efficient industries and builds a culture with reasonable systems, a harmonious society, and a healthy ecological environment. This paper aims to use deep learning algorithms to study environmental protection and the optimization of ecological business economic growth from the perspective of sustainable development. In this regard, this paper proposes a theoretical model of environmental regulation, which aids in the study of the sustainable development of the ecological economy. Through experimental analysis, this study determined that the non-renewable resources of the two cities designated M and N dropped from 82% and 99% in 2017 to 78% and 79% in 2021, a decrease of 3% and 20%, respectively. This shows that the non-renewable resources of the four cities in area A generally showed a downward trend. The experimental results show that the deep learning theory and the environmental regulation model play a specific and effective role in the researching of the ecological business economy. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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32 pages, 5619 KiB  
Article
Analysis of Systemic Risk Scenarios and Stabilization Effect of Monetary Policy under the COVID-19 Shock and Pharmaceutical Economic Recession
by Hao Dong, Yingrong Zheng and Na Li
Sustainability 2023, 15(1), 880; https://doi.org/10.3390/su15010880 - 3 Jan 2023
Viewed by 2505
Abstract
The Global Financial Crisis (GFC) will cause turbulence in the pharmaceutical market and the stagnation of market liquidity, leading to a deep recession in the pharmaceutical economy. After the COVID-19 outbreak, the pharmaceutical economic recession and the rising pharmaceutical financial crisis caused by [...] Read more.
The Global Financial Crisis (GFC) will cause turbulence in the pharmaceutical market and the stagnation of market liquidity, leading to a deep recession in the pharmaceutical economy. After the COVID-19 outbreak, the pharmaceutical economic recession and the rising pharmaceutical financial crisis caused by the closure and control of the COVID-19 outbreak in China were important reasons for the accumulation of systemic financial risks in China. To realize the pharmaceutical economy and financial stability, this paper studies the weakening mechanism of the stabilization effect in systemic risk scenarios and analyzes how the evolution of systemic risk under the COVID-19 shock affects the stabilization effect of monetary policy. Under the COVID-19 shock, in the stage of falling China Financial Stress Index (CFSI), the systemic risk is relatively low, and the impact of traditional policy on macroeconomic stability is more significant; in the rising stage of CFSI, the systemic risk is relatively high, and the impact of traditional policy on macroeconomic stability is limited. This paper develops a Time-Varying Modified CRITIC weighting method and constructs a Time-Varying CFSI. This paper identifies systemic risk scenarios under the COVID-19 shock based on the Markov-Switching Mean Heteroskedastic Vector Auto-Regressive (MSMH-VAR) model and evaluates the stabilizing effects of monetary policy in different economic and financial regional systems (normal times and systemic risk scenarios). The results show that in normal times, loose monetary policy increases price levels, and tight monetary policy reduces price levels with a time lag. In systemic risk scenarios under the COVID-19 shock, the easing effect of policy on output growth is relatively small, and tighter policy increases output growth and prices in the short run and increases volatility in output growth and price levels in the long run. That is, under the COVID-19 shock in systemic risk scenarios, it is difficult to achieve stable growth and stable prices with monetary policy, and the stabilization effect is weakened. This paper focuses on the relationship between systemic risks, monetary policy, and output stability under the COVID-19 shock, analyzes the weakening of stabilization effects after the crisis, and expands the theoretical path of monetary policy stabilization and enriches the research scope of the new framework. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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13 pages, 576 KiB  
Article
Influence of Organizational Democracy on Organizational Citizenship Behaviors in Digital Transformation: Mediating Effects of Job Satisfaction and Organizational Commitment for Smart Services
by Enver Haskasap, Tulen Saner, Serife Eyupoglu and Cemre S. Gunsel Haskasap
Sustainability 2023, 15(1), 452; https://doi.org/10.3390/su15010452 - 27 Dec 2022
Cited by 2 | Viewed by 2356
Abstract
This study investigated the influence of organizational democracy on organizational citizenship behaviors in digital transformation, by considering the mediating effects of job satisfaction and organizational commitment for smart services. Exploratory factor analysis (EFA) was conducted to investigate the factors, which was followed by [...] Read more.
This study investigated the influence of organizational democracy on organizational citizenship behaviors in digital transformation, by considering the mediating effects of job satisfaction and organizational commitment for smart services. Exploratory factor analysis (EFA) was conducted to investigate the factors, which was followed by confirmatory factor analysis (CFA) and path analysis to test the hypotheses. The sample consisted of 144 full-time employees of the largest bank in North Cyprus. The findings suggest that organizational democracy had a significant positive direct effect on the job satisfaction and organizational commitment, whereas the direct effect on the organizational citizenship behaviors was not significant. The mediating effect of organizational commitment was found to be significantly positive. Job satisfaction was found not to be a significant mediator. The indirect effect of organizational democracy on the organizational citizenship behaviors was significant. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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27 pages, 2697 KiB  
Article
Smart Space Design–A Framework and an IoT Prototype Implementation
by Badr Alsamani, Samir Chatterjee, Ali Anjomshoae and Peter Ractham
Sustainability 2023, 15(1), 111; https://doi.org/10.3390/su15010111 - 21 Dec 2022
Cited by 3 | Viewed by 1843
Abstract
In the last decade, the need for smart-space design has been on the rise. Various data collected from Internet-of-Things (IoT) and sensors are used to optimize the operation of smart spaces, which, in urban areas, are evolving into smart cities. How can smart [...] Read more.
In the last decade, the need for smart-space design has been on the rise. Various data collected from Internet-of-Things (IoT) and sensors are used to optimize the operation of smart spaces, which, in urban areas, are evolving into smart cities. How can smart spaces provide value to citizens? There is a need to develop smart services that leverage emerging technologies while taking an inclusive and empowering approach to the inhabitants. To address this need, we present a framework for designing smart spaces and we use a bottom-up (inclusive) approach to instantiate a smart kiosk (SK). The SK prototype provides a practical approach for transforming a traditional building into a smart space utilizing IoT and artificial intelligence technologies. The design science research (DSR) methodology was followed for designing and evaluating the prototype. An iterative process that involves occupant feedback and brainstorming sessions coupled with a literature review was carried out to identify the issues and services related to a smart building. The SK prototype implements three intelligent services that were prioritized by the citizens of the building. The results show that the SK has a high usage and acceptance rate and it can transform a lobby into a highly engaged and smart building space. The prototyping process suggests important factors to ideate and assess smart services and shows that small-scale projects can be successful to enable smart buildings. The framework provides a theoretical contribution while the design and development process assists practitioners in identifying and developing intelligent services based on IoT technology. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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15 pages, 2289 KiB  
Article
IoMT-Based Automated Diagnosis of Autoimmune Diseases Using MultiStage Classification Scheme for Sustainable Smart Cities
by Divya Biligere Shivanna, Thompson Stephan, Fadi Al-Turjman, Manjur Kolhar and Sinem Alturjman
Sustainability 2022, 14(21), 13891; https://doi.org/10.3390/su142113891 - 26 Oct 2022
Cited by 2 | Viewed by 1536
Abstract
The resolution of complex medical diagnoses using pattern recognition requires an artificial neural network-based expert system to automate autoimmune disease diagnosis in blood samples. This process is done using image-based computer-aided diagnosis (CAD) to reduce errors in the diagnosis process. This paper describes [...] Read more.
The resolution of complex medical diagnoses using pattern recognition requires an artificial neural network-based expert system to automate autoimmune disease diagnosis in blood samples. This process is done using image-based computer-aided diagnosis (CAD) to reduce errors in the diagnosis process. This paper describes a Multistage Classification Scheme (MSCS), which uses antinuclear antibody (ANA) tests to identify and classify the existence of autoantibodies in the blood serum that bind to antigens found in the nuclei of mammalian cells. The MSCS classified HEp-2 cells into three stages by using Binary Tree (BT), Artificial Neural Network (ANN), and Support Vector Machine (SVM) as basic blocks. The Indirect Immunofluorescence (IIF) technique is used in the ANA test with Human Epithelial type-2 (HEp-2) cells as substrates. The efficiency of the proposed methodology is assessed using the dataset of ICPR 2016. The intermediate cells (IMC) and positive cells (PC) were separated in Stage 1 prior to preprocessing based on their total strength, and special preprocessing is applied to intermediate cells for improved output, and positive cells are subjected to mild preprocessing. The mean class accuracy (MCA) was 84.9% for intermediate cells and 95.8% for positive cells, although the carefully picked 24 features and SVM classifier were applied. ANN showed better performance by adjusting the weights using the SCGBP algorithm. So, the MCA is 88.4% and 97.1% for intermediate and positive cells, respectively. BT had an MCA of 95.3% for intermediate and 98.6% for positive. In Stage 2, the meta learners BT2, ANN2, and SVM2 were trained for an augmented feature set (24 + 3 results from base learners). Therefore, the performance of BT2, ANN2, and SV M2 was increased by 1.8%, 4.5%, and 4.1% as compared to Stage 1. In Stage 3, the final prediction was performed by majority voting among the results of the three meta learners to achieve 99.1% MCA. The proposed algorithm can be embedded into a CAD framework built for the ANA examination. The proposed model will improve operational efficiency, decrease medical expenses, expand accessibility to healthcare, and improve patient safety in the sector, enabling enterprises to lower unplanned downtime, develop new products or services, increase operational effectiveness, and enhance risk management. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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10 pages, 1668 KiB  
Article
Computer-Vision-Based Statue Detection with Gaussian Smoothing Filter and EfficientDet
by Mubarak Auwalu Saleh, Zubaida Said Ameen, Chadi Altrjman and Fadi Al-Turjman
Sustainability 2022, 14(18), 11413; https://doi.org/10.3390/su141811413 - 12 Sep 2022
Cited by 2 | Viewed by 1896
Abstract
Smart tourism is a developing industry, and numerous nations are planning to establish smart cities in which technology is employed to make life easier and link nearly everything. Many researchers have created object detectors; however, there is a demand for lightweight versions that [...] Read more.
Smart tourism is a developing industry, and numerous nations are planning to establish smart cities in which technology is employed to make life easier and link nearly everything. Many researchers have created object detectors; however, there is a demand for lightweight versions that can fit into smartphones and other edge devices. The goal of this research is to demonstrate the notion of employing a mobile application that can detect statues efficiently on mobile applications, and also improve the performance of the models by employing the Gaussian Smoothing Filter (GSF). In this study, three object detection models, EfficientDet—D0, EfficientDet—D2 and EfficientDet—D4, were trained on original and smoothened images; moreover, their performance was compared to find a model efficient detection score that is easy to run on a mobile phone. EfficientDet—D4, trained on smoothened images, achieves a Mean Average Precision (mAP) of 0.811, an mAP-50 of 1 and an mAP-75 of 0.90. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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11 pages, 1577 KiB  
Article
Vehicle Price Classification and Prediction Using Machine Learning in the IoT Smart Manufacturing Era
by Fadi Al-Turjman, Adedoyin A. Hussain, Sinem Alturjman and Chadi Altrjman
Sustainability 2022, 14(15), 9147; https://doi.org/10.3390/su14159147 - 26 Jul 2022
Cited by 9 | Viewed by 3036
Abstract
In this paper, machine learning (ML) strategies have been utilized in predicting vehicles’ prices and good deals. Vehicle value prediction has been considered one of the most significant research topics with the rise of IoT for sustainability. This is because it requires observable [...] Read more.
In this paper, machine learning (ML) strategies have been utilized in predicting vehicles’ prices and good deals. Vehicle value prediction has been considered one of the most significant research topics with the rise of IoT for sustainability. This is because it requires observable exertion and massive field information. Towards generating a model that anticipates the vehicles’ price, we applied three ML methods (neural network, decision tree, support vector machine, and linear regression). However, the referenced methods have been applied to function together as a group in a hybrid model. The information utilized was gathered from an information and computer science school that houses different datasets. Separate exhibitions of several ML techniques were contrasted to reveal which one is suitable for the accessible information index. Various difficulties and challenges associated with this design have also been discussed. Moreover, the model was experimented, and a 90% precision was achieved. This potential result can help in providing precise vehicle deals in the emerging Internet of Things (IoT) for the sustainability paradigm. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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22 pages, 8875 KiB  
Article
Cognitive IoT Vision System Using Weighted Guided Harris Corner Feature Detector for Visually Impaired People
by Manoranjitham Rajendran, Punitha Stephan, Thompson Stephan, Saurabh Agarwal and Hyunsung Kim
Sustainability 2022, 14(15), 9063; https://doi.org/10.3390/su14159063 - 24 Jul 2022
Viewed by 1461
Abstract
India has an estimated 12 million visually impaired people and is home to the world’s largest number in any country. Smart walking stick devices use various technologies including machine vision and different sensors for improving the safe movement of visually impaired persons. In [...] Read more.
India has an estimated 12 million visually impaired people and is home to the world’s largest number in any country. Smart walking stick devices use various technologies including machine vision and different sensors for improving the safe movement of visually impaired persons. In machine vision, accurately recognizing an object that is near to them is still a challenging task. This paper provides a system to enable safe navigation and guidance for visually impaired people by implementing an object recognition module in the smart walking stick that uses a local feature extraction method to recognize an object under different image transformations. To provide stability and robustness, the Weighted Guided Harris Corner Feature Detector (WGHCFD) method is proposed to extract feature points from the image. WGHCFD discriminates image features competently and is suitable for different real-world conditions. The WGHCFD method evaluates the most popular Oxford benchmark datasets, and it achieves greater repeatability and matching score than existing feature detectors. In addition, the proposed WGHCFD method is tested with a smart stick and achieves 99.8% recognition rate under different transformation conditions for the safe navigation of visually impaired people. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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17 pages, 690 KiB  
Article
Cluster-Based Routing Protocol with Static Hub (CRPSH) for WSN-Assisted IoT Networks
by Rakesh Kumar Lenka, Manjur Kolhar, Hitesh Mohapatra, Fadi Al-Turjman and Chadi Altrjman
Sustainability 2022, 14(12), 7304; https://doi.org/10.3390/su14127304 - 15 Jun 2022
Cited by 27 | Viewed by 2267
Abstract
The Internet of Things (IoT) is an evolving concept that has achieved prominence in the modern era. An autonomous sensor-equipped device is the major component of WSN-assisted IoT infrastructure. These devices intelligently sense the environment, automatically collect the data, and deliver the information [...] Read more.
The Internet of Things (IoT) is an evolving concept that has achieved prominence in the modern era. An autonomous sensor-equipped device is the major component of WSN-assisted IoT infrastructure. These devices intelligently sense the environment, automatically collect the data, and deliver the information to paired devices. However, in WSN-assisted IoT networks, energy depletion and hardware faults might result in device failures. Additionally, this might affect data transmission. A reliable route significantly reduces data retransmissions, which can help in congestion reduction and energy conservation. Generally, the sensor devices are typically deployed densely throughout the WSN-assisted IoT networks. A high number of sensor devices covering a monitoring area might result in duplicate data. The clustering method can be used to overcome this problem. The clustering technique reduces network traffic, whereas the multipath technique ensures path reliability. In CRPSH, we used the clustering technique to reduce the duplicate data. Moreover, the multipath approach can increase the reliability of the proposed protocol. CRPSH is intended to minimize the overhead associated with control packets and extend the network’s lifetime. The complete set of simulations is carried out using the Castalia simulator. The proposed protocol is found to reduce energy consumption and increase the lifetime of IoT infrastructure networks. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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14 pages, 6090 KiB  
Article
Retrofitting Existing Buildings to Improve Energy Performance
by Sunil Kumar Sharma, Swati Mohapatra, Rakesh Chandmal Sharma, Sinem Alturjman, Chadi Altrjman, Leonardo Mostarda and Thompson Stephan
Sustainability 2022, 14(2), 666; https://doi.org/10.3390/su14020666 - 7 Jan 2022
Cited by 28 | Viewed by 4896
Abstract
Energy-efficient retrofits embrace enhancement of the building envelope through climate control strategies, employment of building-integrated renewable energy technologies, and insulation for a sustainable city. Building envelope improvements with insulation is a common approach, yet decision-making plays an important role in determining the most [...] Read more.
Energy-efficient retrofits embrace enhancement of the building envelope through climate control strategies, employment of building-integrated renewable energy technologies, and insulation for a sustainable city. Building envelope improvements with insulation is a common approach, yet decision-making plays an important role in determining the most appropriate envelope retrofit strategy. In this paper, the main objective is to evaluate different retrofit strategies (RS) through a calibrated simulation approach. Based on an energy performance audit and monitoring, an existing building is evaluated on performance levels and improvement potentials with basic energy conservation measures. The considered building is experimentally monitored for a full year, and monitoring data are used in calibrating the simulation model. The validation of the base model is done by comparing the simulation analysis with the experimental investigation, and good agreement is found. Three different retrofit strategies based on Intervention of minor (RS1), Moderate (RS2), and Major (RS3) are analyzed and juxtaposed with the base model to identify the optimal strategy of minimizing energy consumption. The result shows that total energy intensity in terms of the percentage reduction index is about 16.7% for RS1, 19.87 for RS2, and 24.12% for RS3. Hence, RS3 is considered the optimal retrofit strategy and is further simulated for a reduction in carbon dioxide (CO2) emissions and payback investigation. It was found that the annual reduction in CO2 emissions of the building was 18.56%, and the payback period for the investment was 10.6 years. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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37 pages, 22255 KiB  
Article
Blockchain-Based Community Safety Security System with IoT Secure Devices
by Chin-Ling Chen, Zi-Yi Lim and Hsien-Chou Liao
Sustainability 2021, 13(24), 13994; https://doi.org/10.3390/su132413994 - 18 Dec 2021
Cited by 3 | Viewed by 3111
Abstract
Humans frequently need to construct a huge number of buildings for occupants in large cities to work or live in a highly developed civilization; people who live in the same building or same area are defined as a community. A thief stealing items, [...] Read more.
Humans frequently need to construct a huge number of buildings for occupants in large cities to work or live in a highly developed civilization; people who live in the same building or same area are defined as a community. A thief stealing items, a burglary, fire hazards, flood hazards, earthquakes, emergency aid, abnormal gas leakage, strange behavior, falling in a building, fainting in a building, and other incidents all threaten the community’s safety. Therefore, we proposed a blockchain-based community safety security system that is combined with IoT devices. In the proposed scheme, we designed multiple phases to process the alarm triggered by IoT devices. IoT devices can be set up in two types areas: private and public areas. Both types of IoT devices’ alarms have different process flow for the response and records checking phase. All records are saved in the Blockchain Center to assure the data can be verified and cannot be forged. During the communication between sender and receiver, we implemented some security methods to prevent message repudiation, prevent transmission intercept, prevent replay attacks, and ensure data integrity. We also implemented a clarifying mechanism to ensure that all system participants can have confidence in the system’s processing methods. The proposed scheme can be used in communities to improve community safety and prevent unnecessary conflicts. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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35 pages, 2640 KiB  
Article
Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China
by Ke Wang, Yafei Zhao, Rajan Kumar Gangadhari and Zhixing Li
Sustainability 2021, 13(19), 10983; https://doi.org/10.3390/su131910983 - 3 Oct 2021
Cited by 26 | Viewed by 8145
Abstract
Smart cities play a vital role in the growth of a nation. In recent years, several countries have made huge investments in developing smart cities to offer sustainable living. However, there are some challenges to overcome in smart city development, such as traffic [...] Read more.
Smart cities play a vital role in the growth of a nation. In recent years, several countries have made huge investments in developing smart cities to offer sustainable living. However, there are some challenges to overcome in smart city development, such as traffic and transportation management, energy and water distribution and management, air quality and waste management monitoring, etc. The capabilities of the Internet of Things (IoT) and artificial intelligence (AI) can help to achieve some goals of smart cities, and there are proven examples from some cities like Singapore, Copenhagen, etc. However, the adoption of AI and the IoT in developing countries has some challenges. The analysis of challenges hindering the adoption of AI and the IoT are very limited. This study aims to fill this research gap by analyzing the causal relationships among the challenges in smart city development, and contains several parts that conclude the previous scholars’ work, as well as independent research and investigation, such as data collection and analysis based on DEMATEL. In this paper, we have reviewed the literature to extract key challenges for the adoption of AI and the IoT. These helped us to proceed with the investigation and analyze the adoption status. Therefore, using the PRISMA method, 10 challenges were identified from the literature review. Subsequently, determination of the causal inter-relationships among the key challenges based on expert opinions using DEMATEL is performed. This study explored the driving and dependent power of the challenges, and causal relationships between the barriers were established. The results of the study indicated that “lack of infrastructure (C1)”, ”insufficient funds (C2)”, “cybersecurity risks (C3)”, and “lack of trust in AI, IoT” are the causal factors that are slowing down the adoption of AI and IoT in smart city development. The inter-relationships between the various challenges are presented using a network relationship map, cause–effect diagram. The study’s findings can help regulatory bodies, policymakers, and researchers to make better decisions to overcome the challenges for developing sustainable smart cities. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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26 pages, 2193 KiB  
Article
An Attribute-Based Access Control for IoT Using Blockchain and Smart Contracts
by Syed Yawar Abbas Zaidi, Munam Ali Shah, Hasan Ali Khattak, Carsten Maple, Hafiz Tayyab Rauf, Ahmed M. El-Sherbeeny and Mohammed A. El-Meligy
Sustainability 2021, 13(19), 10556; https://doi.org/10.3390/su131910556 - 23 Sep 2021
Cited by 26 | Viewed by 4790
Abstract
With opportunities brought by the Internet of Things (IoT), it is quite a challenge to maintain concurrency and privacy when a huge number of resource-constrained distributed devices are involved. Blockchain have become popular for its benefits, including decentralization, persistence, immutability, auditability, and consensus. [...] Read more.
With opportunities brought by the Internet of Things (IoT), it is quite a challenge to maintain concurrency and privacy when a huge number of resource-constrained distributed devices are involved. Blockchain have become popular for its benefits, including decentralization, persistence, immutability, auditability, and consensus. Great attention has been received by the IoT based on the construction of distributed file systems worldwide. A new generation of IoT-based distributed file systems has been proposed with the integration of Blockchain technology, such as the Swarm and Interplanetary File System. By using IoT, new technical challenges, such as Credibility, Harmonization, large-volume data, heterogeneity, and constrained resources are arising. To ensure data security in IoT, centralized access control technologies do not provide credibility. In this work, we propose an attribute-based access control model for the IoT. The access control lists are not required for each device by the system. It enhances access management in terms of effectiveness. Moreover, we use blockchain technology for recording the attribute, avoiding data tempering, and eliminating a single point of failure at edge computing devices. IoT devices control the user’s environment as well as his or her private data collection; therefore, the exposure of the user’s personal data to non-trusted private and public servers may result in privacy leakage. To automate the system, smart contracts are used for data accessing, whereas Proof of Authority is used for enhancing the system’s performance and optimizing gas consumption. Through smart contracts, ciphertext can be stored on a blockchain by the data owner. Data can only be decrypted in a valid access period, whereas in blockchains, the trace function is achieved by the storage of invocation and the creation of smart contracts. Scalability issues can also be resolved by using the multichain blockchain. Eventually, it is concluded from the simulation results that the proposed system is efficient for IoT. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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16 pages, 584 KiB  
Article
Load Balancing Algorithm on the Immense Scale of Internet of Things in SDN for Smart Cities
by Himanshi Babbar, Shalli Rani, Divya Gupta, Hani Moaiteq Aljahdali, Aman Singh and Fadi Al-Turjman
Sustainability 2021, 13(17), 9587; https://doi.org/10.3390/su13179587 - 26 Aug 2021
Cited by 23 | Viewed by 2818
Abstract
Since the worldwide Internet of Things (IoT) in smart cities is becoming increasingly popular among consumers and the business community, network traffic management is a crucial issue for optimizing the IoT ’s performance in smart cities. Multiple controllers on a immense scale implement [...] Read more.
Since the worldwide Internet of Things (IoT) in smart cities is becoming increasingly popular among consumers and the business community, network traffic management is a crucial issue for optimizing the IoT ’s performance in smart cities. Multiple controllers on a immense scale implement in Software Defined Networks (SDN) in integration with Internet of Things (IoT) as an emerging paradigm enhances the scalability, security, privacy, and flexibility of the centralized control plane for smart city applications. The distributed multiple controller implementation model in SDN-IoT cannot conform to the dramatic developments in network traffic which results in a load disparity between controllers, leading to higher packet drop rate, high response time, and other problems with network performance deterioration. This paper lays the foundation on the multiple distributed controller load balancing (MDCLB) algorithm on an immense-scale SDN-IoT for smart cities. A smart city is a residential street that uses information and communication technology (ICT) and the Internet of Things (IoT) to improve its citizens’ quality of living. Researchers then propose the algorithm on the unbalancing of the load using the multiple controllers based on the parameter CPU Utilization in centralized control plane. The experimental results analysis is performed on the emulator named as mininet and validated the results in ryu controller over dynamic load balancing based on Nash bargaining, efficient switch migration load balancing algorithm, efficiency aware load balancing algorithm, and proposed algorithm (MDCLB) algorithm are executed and analyzed based on the parameter CPU Utilization which ensures that the Utilization of CPU with load balancing is 20% better than the Utilization of CPU without load balancing. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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13 pages, 1107 KiB  
Article
Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking
by Himanshi Babbar, Shalli Rani, Aman Singh, Mohammed Abd-Elnaby and Bong Jun Choi
Sustainability 2021, 13(16), 8910; https://doi.org/10.3390/su13168910 - 9 Aug 2021
Cited by 15 | Viewed by 2837
Abstract
The network session constraints for Industrial Internet of Things (IIoT) applications are different and challenging. These constraints necessitates a high level of reconfigurability, so that the system can assess the impact of an event and adjust the network effectively. Software Defined Networking (SDN) [...] Read more.
The network session constraints for Industrial Internet of Things (IIoT) applications are different and challenging. These constraints necessitates a high level of reconfigurability, so that the system can assess the impact of an event and adjust the network effectively. Software Defined Networking (SDN) in contrast to existing networks segregates the control and data plane to support network configuration which is programmable with smart cities requirement that shows the highest impact on the system but faces the problem of reliability. To address this issue, the SDN-IIoT based load balancing algorithm is proposed in this article and it is not application specific.Quality of service (QoS) aware architecture i.e., SDN-IIoT load balancing scheme is proposed and it deals with load on the servers. Huge load on the servers, makes them vulnerable to halt the system and hence leads to faults which creates the reliability problem for real time applications. In this article, load is migrated from one server to another server, if load on one server is more than threshold value. Load distribution has made the proposed scheme more reliable than already existing schemes. Further, the topology used for the implementation has been designed using POX controller and the results has been evaluated using Mininet emulator with its support in python programming. Lastly, the performance is evaluated based on the various Quality of Service (QoS) metrics; data transmission, response time and CPU utilization which shows that the proposed algorithm has shown 10% improvement over the existing LBBSRT, Random, Round-robin, Heuristic algorithms. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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Review

Jump to: Research

36 pages, 6815 KiB  
Review
Revolutionary Strategies Analysis and Proposed System for Future Infrastructure in Internet of Things
by Arun Kumar, Sharad Sharma, Aman Singh, Ayed Alwadain, Bong-Jun Choi, Jose Manual-Brenosa, Arturo Ortega-Mansilla and Nitin Goyal
Sustainability 2022, 14(1), 71; https://doi.org/10.3390/su14010071 - 22 Dec 2021
Cited by 18 | Viewed by 4680
Abstract
The Internet of Things (IoT) has changed the worldwide network of people, smart devices, intelligent things, data, and information as an emergent technology. IoT development is still in its early stages, and numerous interrelated challenges must be addressed. IoT is the unifying idea [...] Read more.
The Internet of Things (IoT) has changed the worldwide network of people, smart devices, intelligent things, data, and information as an emergent technology. IoT development is still in its early stages, and numerous interrelated challenges must be addressed. IoT is the unifying idea of embedding everything. The Internet of Things offers a huge opportunity to improve the world’s accessibility, integrity, availability, scalability, confidentiality, and interoperability. However, securing the Internet of Things is a difficult issue. The IoT aims to connect almost everything within the framework of a common infrastructure. This helps in controlling devices and, will allow device status to be updated everywhere and at any time. To develop technology via IoT, several critical scientific studies and inquiries have been carried out. However, many obstacles and problems remain to be tackled in order to reach IoT’s maximum potential. These problems and concerns must be taken into consideration in different areas of the IoT, such as implementation in remote areas, threats to the system, development support, social and environmental impacts, etc. This paper reviews the current state of the art in different IoT architectures, with a focus on current technologies, applications, challenges, IoT protocols, and opportunities. As a result, a detailed taxonomy of IoT is presented here which includes interoperability, scalability, security and energy efficiency, among other things. Moreover, the significance of blockchains and big data as well as their analysis in relation to IoT, is discussed. This article aims to help readers and researchers understand the IoT and its applicability to the real world. Full article
(This article belongs to the Special Issue The Role and Impact of the Internet of Things (IoT) in Sustainable Smart Cities)
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