Smart Sustainable Cities Research Articles

Digital Transformation: towards Sustainable and Smart New Cities in Upper Egypt (New Qena Case study).

Despite the ongoing development of IT and innovative technologies in all aspects of life, the transformation of cities into smart, sustainable cities is still at a starting level in developing countries. Decision-makers and planners still face numerous challenges in achieving smart, sustainable cities in Egypt. Such as rapid urbanization, increased emission rate, waste of resources, population growth, weak infrastructure, etc. This has led many countries to accelerate the harnessing of technology’s potential for transformation into smart, sustainable cities. Therefore, the research aims to investigate and highlight the significance of innovative technologies in driving and achieving digital transformation in new cities in Upper Egypt to become smart, sustainable cities. That could lead the cities to invest and build the qualifications to be autonomous cities in the future. The research studied three cases in the Arab world in order to apply the lessons acquired from their digital transformation experiences and sustainable plans. Consequently, the paper presents proposed guidelines to achieve a sustainable smart city in New Qena. These guidelines assist planners, authorities, and decision-makers in improving the quality of life, and city services, enhancing economic and social sustainability, promoting climate-friendly environments, and developing a vision for the future transformation of the city.

Sustainable Smart City to Society 5.0: State-of-the-Art and Research Challenges

With the growth of data traffic, demand of huge number of digital devices and their interconnection to establish a reliable communication, the internet has become a potential demand of the society. To develop a system that securely connects the internet to real-world space would aid in the advancement of a human-centered society that balances economic progress with the resolution of social issues. This paper provides a detailed aspect of Society 5.0 with its requirements, architecture, and components. We have proceeded extensively with the state-of-the-art Society 5.0 and its link with Industry 4.0/5.0. Furthermore, the role of Society 5.0 in the sustainable development goals of the United Nations is well elaborated. Several emerging communication and computing technologies such 5G/5G-Internet of Things (IoT), edge computing/ cloud computing/ fog computing, Internet of everything, blockchain, and beyond networks have been also well explored to fulfill the demands of Society 5.0. The potential application of super smart cities (Society 5.0) with some real-time experience of inhabitants is thoroughly discussed. Finally, we highlighted several open research challenges with opportunities.

A role distinguishing Bert model for medical dialogue system in sustainable smart city

Smart medicine is a vital component for building sustainable smart city. In smart medicine, intelligent dialogue system is playing an important role in providing personalized and efficient healthcare services to improve the quality of life for human beings. The Bert model has become a popular way to construct intelligent medical dialogue system. However, the current Bert model is difficult to achieve desirable results for this task since its input does not reflect the difference in roles. To overcome this drawback, we present a role distinguishing Bert model for intelligent medical dialogue system to help construct the sustainable smart city. Particularly, we segment and label the utterances depending on different dialogue roles, and then construct the corresponding segment embedding as the input of our model. Furthermore, we substitute the NSP task with the SOP task to better learn the coherence between sentences. Finally, we verify the proposed model by comparing it with Ernie on some online E-commerce datasets for intent recognition, semantic matching, and session dialogue classification. The results demonstrate that our proposed model improves the average 1% accuracy for different tasks in dialogue system, proving the potential of the proposed model for establishing intelligent medical dialogue system in smart city.

Sustainability of Smart Cities in Malaysia and the Philippines using ESG Model

Using the environmental, social and governance (ESG) model, this study examines the sustainability of local communities living in smart cities in Malaysia and the Philippines. Self-administered questionnaires were distributed to 400 respondents living in smart cities in Malaysia and the Philippines. PLS-SEM was used to analyse the data using the Singapore smart city initiatives framework. Findings show that local communities' awareness, perception and readiness to participate in the smart city initiatives impact smart city sustainability. In line with SDG 11, towards a more sustainable city, the study provides micro-level data to show the significance of local communities who are ultimately the end-users. Keywords: smart cities, benchmarking, quality of life, SDG 11 eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i22.4157

The Concept of a Smart City in the Context of Modern Research

It was defined that a smart city is a concept of city development that involves the integration of the newest information and communication technologies in all spheres of its functioning. It was found that the components of a smart city are: smart infrastructure, smart transport, smart energy, smart health care, smart governance, smart economy, smart citizens, smart technologies. The attributes of a smart city are: sustainability, quality of life, urbanization, smartness. It was determined that the main directions of development of a smart city are society, economy, environment, governance. It was found that the main challenges of implementing the concept of a smart city are: the cost of smart city projects, the integration of ICT and physical infrastructure, the amount of data that creates a smart city, operational efficiency, the level of hydrocarbon emissions, achieving sustainability, information security, protection from natural disasters cataclysms. It was found that smart city sustainability is linked to urban infrastructure, governance, energy, climate change, pollution, waste, as well as social, economic and health issues. It was determined that the Internet of Things and big data are the most important elements of implementing the concept of a smart city. Using the Internet of Things makes smart cities possible. The main components of the Internet of Things are: an item, local network, Internet, cloud. Big data is a collection of complex data sets that are difficult to process using conventional database management tools or traditional data processing applications. It was found that the Internet of Things, big data and smart cities are closely related. The data generated by a smart city and associated with spatial and temporal tags form the basis of big data. Big data in smart cities is accumulated as a result of the work of Internet of Things sensors, websites, mobile applications, and social networks.

Italians and smart working: A technical study on the effects of smart working on the society

Due to the COVID-19 pandemic, “smart working” (hereafter SW) has become the norm for millions of workers around the world. A new way of working for most workers and in particular in Italy, a country where the use of SW was extremely rare before the pandemic. The aim of this paper, was to highlights whether smart working, adopted to face and survive global crises, could be really a suitable tool to generate benefits for companies, society, reduce environmental impacts and guarantee autonomy and flexibility for workers as well as a balance between private life. The analysis was conducted on a sample of 2753 individuals based in Italy during the period January and February 2021 using PLS-SEM model. The contribution of this study to research is identified in clarifying the potential of SW to create sustainable Smart Cities.

Developing DPSIR Framework for Managing Climate Change in Urban Areas: A Case Study in Jakarta, Indonesia

From an environmentally conscious and ecological perspective, the sustainability of cities within the effects of climate change are closely related to the wise use of resources and modifications in the ecological status of the environment. In terms of the ecological environment, the sustainability of smart cities entails meeting present and future societal demands for the environment of the water, land, and air, among others. Environmental and the ecological concerns that arise from rapid climate change and monetary developments are shown in the inconsistency between ecological assets, environmental pollution, and the destruction of nature. In this study, the authors aim to develop a strategy to deal with climate change in urban areas using Remote Sensing and the Driver-Pressure-State-Impact-Response (DPSIR) Framework with a case study in Jakarta Smart City. The DPSIR framework, which will be developed and implemented in the city of Jakarta, is a smarter and more sustainable framework that is evaluated through a systematic evaluation of sustainability with quantitative research using the entropy weight method and Partial Least Square-Structural Equation Modeling (PLS-SEM). These methods evaluate 58 representative elements of environments at the urban level, including the shortcomings of earlier research such as data availability, spatial and temporal constraints, and several related ecological indicators, such as soil pH, wind speed, air quality index as well as land changes in the spatial (spatiotemporal) time series. The results of the study show that in the metropolitan city of Jakarta, the Drivers that are related to climate change are the rate of population growth and the rate of industrial growth which, although increases people’s income and GRDP in Jakarta; it also creates Pressures, namely an increase in the amount of water consumption and in the amount of wastewater. Based on these pressures, the environmental conditions (State) of Jakarta city have undergone several environmental changes, such as loss of water supply, changes in wind speed, changes in rainfall, and increasing concentrations of the Air Pollutant Standard Index. The Impact of these three elements resulted in the increase in household and industrial water consumption, an increase in annual electricity consumption, and deteriorating air quality. Hence, the Response to these four interrelated causal variables is that the Jakarta Provincial Government must increase annual funds for the construction of urban community facilities, increase the production capacity of clean water supply, build environment-friendly wastewater treatment facilities, increase the capacity of waste processing infrastructure and transportation fleets, and educate people to use water wisely to reduce the level of water use.

Bridging ‘Stakeholder Value Creation’ and ‘Urban Sustainability’: The need for better integrating the Environmental Dimension

Stakeholder-orientation is critical to fostering sustainable urban development through synergic collaborations among urban stakeholders. However, although Stakeholder Value Creation (SVC) has been widely explored in sustainable organizations, little attention has been given to SVC in Urban Sustainability. Thus, this research explored the conceptual connections between SVC and Urban Sustainability using a new methodological protocol based on a Sequential Mixed Method Research design. The main findings revealed that the social, economic, and institutional dimensions of Urban Sustainability are fully integrated into the SVC framework; however, better integration of the Environmental Dimension is needed. Therefore, this dyadic phenomenon can currently be classified as unsustainable or weak sustainability. Additionally, the critical characteristics of SVC with Urban Sustainability are: stakeholder engagement; stakeholder cooperation; ethics of capitalism; satisfaction of stakeholders' needs by self-organization and learning capacities, diversity, trust, common meaning, and consensus; sustainable economic development; innovation ecosystems; sharing economy; circular economy; technical resources; social capital; smart sustainable cities; and energy efficiency. Finally, we proposed a framework for Sustainable SVC in Cities, in which SVC is a means for achieving Urban Sustainability and better integrating the environmental dimension. Environmental issues, environmental management, social entrepreneurship, non-human stakeholders, and stakeholder proximity are promising perspectives in the framework.

Selection of IoT service provider for sustainable transport using q-rung orthopair fuzzy CRADIS and unknown weights

Internet-of-things (IoT) is a fast-growing technology and sustainable transportation is a crucial application area of IoTs. Selecting an appropriate IoT service provider (IoTSP) is cumbersome and viewed as a multi-criteria decision problem. Recent studies on IoTSP selection inferred that uncertainty and subjectivity during preference elicitation are not flexibly handled. Moreover, they mentioned hesitation and interrelationship are crucial behaviors to be modeled. Motivated by the inferences, this research aims to develop an integrated framework with q-rung orthopair fuzzy sets (q-ROFSs) to evaluate IoTSPs. In this line, the CRITIC method is presented for experts’ importance determination under the q-ROF context. Later, Cronbach’s measure is used for criteria weight calculation with q-ROFSs. Also, an algorithm for prioritization is developed by extending the CRADIS formulation. Lastly, the proposed framework is testified through a case example of IoTSP selection for smart city utilities in India. Results infer that availability, total cost, and security/privacy are crucial criteria for evaluating IoTSPs. Sensitivity and comparison analysis is further conducted to determine the framework’s robustness. This study can assist urban planners, politicians, and other stakeholders in selecting proper IoTSPs when forming sustainable smart cities.

Backcasting frugally innovative smart sustainable future cities

This paper envisions alternative scenarios for future cities that are resilient environmentally, socially, economically, and embedded in smart infrastructure and governance. It reinforces the position that although complementary, the backcasting approach is more appropriate for future city planning. There is limited research that envisions how future cities can be backcasted with frugal innovation (FI) underpinning the sustainability pillars. This research aims to narrow the gap. The methodology is based on a systematic literature review and secondary exploratory case studies. The results of the TOWS (threats, opportunities, weaknesses, strengths) analysis on the suitability of FI on smart sustainable cities (SSC) developmental policies show that FI is an affordable and inclusive way to sustainably develop cities without injury to the environment. The findings reveal that the five pillars of a smart sustainable future city can integrate frugal innovation and lean engineering concepts to ensure sustainable development at lower costs. Through frugal innovation embedded in city infrastructure, cleaner methods of production can be realized, and inclusiveness can be fostered.

SMART VILLAGE DESIGN USING INDONESIAN GOVERNMENT ENTERPRISE ARCHITECTURE

Almost all aspects of life require information technology, starting from aspects of primary, secondary, and tertiary needs. Digital technology and innovation can support quality of life, higher standards of living, better public services for the community, and better use of resources to become new opportunities for a rural value chain in terms of better products and processes. Smart village is the concept of developing an independent village by providing services. Implementing smart villages will be the right solution to building a formidable and sustainable smart city to improve the quality of public resources and services. IGEA framework (Indonesian Government Enterprise Architecture Framework) is designed to build an enterprise architecture at the Indonesian government level to support the development of IT services to be better, more efficient, and effective. The phases used in architectural design using IGEA are the Preliminary Phase, Architecture Vision, Business architecture, Data Architecture, Application Architecture, and Technology Architecture. This study aims to analyze, design, and produce a blueprint for Enterprise Architecture by applying the smart village concept to overcome public service problems and improve the quality of apparatus resources and accountable governance in public services. The scope of this research is only in the preliminary phase of the business architecture. The result is architecture principle, goals, vision and mission, policy and regulation, solution concept diagram, and improvement of twelve business processes, and public service catalog.

A neuro evolutionary scheme for improved IoT energy efficiency in smart cities

With the emergence of Internet of Things (IoT) and allied applications for smart cities, sustainability goals have seen a prominent emphasis. This paper focuses on the energy efficiency aspect of such sustainable smart city goals. Although energy efficiency has been studied at different levels of a smart city’s Information and Communication Technology (ICT) infrastructure, this paper specially focuses on device level energy minimization strategy by means of modelling the energy consumption while accounting for the Clusterheads (CluH) and duty cycling and thereby using evolutionary algorithms. In this paper, a Genetic Algorithm (GA) and a hybrid Artificial Neural Network based Particle Swarm Optimization (PSO), namely Feed Forward Neural Network based PSO(FFNN-PSO) has been used to solve the energy minimization problem. Simulation experiments carried out for different scenarios with varying configuration demonstrate the efficacy of the hybrid neuro evolutionary scheme.

Aquila Optimization with Transfer Learning Based Crowd Density Analysis for Sustainable Smart Cities

Video surveillance in smart cities provides efficient city operations, safer communities, and improved municipal services. Object detection is a computer vision-based technology, which is utilized for detecting instances of semantic objects of a specific class in digital videos and images. Crowd density analysis is a widely used application of object detection, while crowd density classification techniques face complications such as inter-scene deviations, non-uniform density, intra-scene deviations and occlusion. The convolution neural network (CNN) model is advantageous. This study presents Aquila Optimization with Transfer Learning based Crowd Density Analysis for Sustainable Smart Cities (AOTL-CDA3S). The presented AOTL-CDA3S technique aims to identify different kinds of crowd densities in the smart cities. For accomplishing this, the proposed AOTL-CDA3S model initially applies a weighted average filter (WAF) technique for improving the quality of the input frames. Next, the AOTL-CDA3S technique employs an AO algorithm with the SqueezeNet model for feature extraction. Finally, to classify crowd densities, an extreme gradient boosting (XGBoost) classification model is used. The experimental validation of the AOTL-CDA3S approach is tested by means of benchmark crowd datasets and the results are examined under distinct metrics. This study reports the improvements of the AOTL-CDA3S model over recent state of the art methods.

Sustainable Smart Cities and Associated Risks – A Review

Sustainable Smart Cities and Associated Risks – A Review

System for Detecting Social Distance During COVID-19 using YOLOv3 and OpenCV

A virus called COVID-19 spreads between people in close proximity via minute droplets created through talking, sneezing, coughing, and most commonly by inhalation. Many people have died as a result of the pandemic’s severe respiratory infection, which is still present today. You can reduce your risk of contracting COVID-19 by avoiding physical contact with others. This study suggests a real-time AI framework for people detection, monitoring social distance violations, and categorising people’s social distances based on live video feeds. In this study, YOLOv3 was suggested for object detection. Its straightforward neural network architecture makes it appropriate for embedded devices that are reasonably priced. Comparing the suggested model to other real-time detection methods, it is a better choice. Additionally, with the aid of OpenCV, an open-source toolkit for computer vision, machine learning, and image processing. The major purpose of the image processing feature is to enhance the image quality so that the AI detection system would accurately recognise human movement. Computer vision is used to analyse photos and videos.The final iteration of the prototype algorithm has been put to use in low-cost CCTV Cameras made up of fixed cameras that are placed in any public area where large crowds used to congregate. The suggested method is appropriate for a surveillance system in sustainable smart cities for people detection, social distance classification, and tracking social dis- tance violations. This will make it easier for the government to understand how people who are socially isolated are doing.

Introducing the Special Issue on Artificial Intelligence Applications for Sustainable Urban Living

All global cities are in the process of transforming from classical cities to sustainable smart cities [...]

Blockchain applications in smart sustainable city context—A systematic mapping study

The advancement in blockchain applications in the smart sustainable city infrastructure is evaluated in this paper through a comprehensive mapping review. The evaluation is carried out by posing four research questions that address current developments in blockchain technology in the context of smart cities and point out areas where additional study is needed. This study also includes a scoping of blockchain applications in a smart city context to highlight the obstacles to incorporating blockchain technology into smart city infrastructure. Finally, some suggestions for overcoming the problems of incorporating blockchain technology with smart city infrastructure are offered. This research will help researchers and policymakers gain a better understanding of blockchain applications in smart cities.

An IPA Approach towards Including Citizens’ Perceptions into Strategic Decisions for Smart Cities in Romania

City administrators have begun to consider citizens’ perception as an essential enabler of smart and sustainable city development. In response to their need, our study mainly aimed to analyze the citizens’ perceptions related to the attributes of a smart city and to offer an evidence-based importance–performance analysis (IPA) technique, revised with triangular number fuzzy, to set priorities to develop it further successfully, taking Oradea, Romania, as an example. Specifically, we investigated varying the citizens’ perceptions regarding the attributes of a smart city across the thematic content analysis followed by an IPA approach to identify the attributes of a smart city that could be expected to advance its future development. The results show that most of our respondents appreciated the city administrators’ efforts and expressed relatively higher preferences for the fifteen smart city attributes of Oradea on which the local authorities should focus. The research brings valuable insight into the strategic decision making related to smart city development, which can serve academics and practitioners, complementing existing literature on the citizens’ perception of sustainable smart city development.

Next-generation energy systems for sustainable smart cities: Roles of transfer learning

Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while improving grid stability and meeting service demand. This is possible by adopting next-generation energy systems, which leverage artificial intelligence, the Internet of things (IoT), and communication technologies to collect and analyze big data in real-time and effectively run city services. However, training machine learning algorithms to perform various energy-related tasks in sustainable smart cities is a challenging data science task. These algorithms might not perform as expected, take much time in training, or do not have enough input data to generalize well. To that end, transfer learning (TL) has been proposed as a promising solution to alleviate these issues. To the best of the authors’ knowledge, this paper presents the first review of the applicability of TL for energy systems by adopting a well-defined taxonomy of existing TL frameworks. Next, an in-depth analysis is carried out to identify the pros and cons of current techniques and discuss unsolved issues. Moving on, two case studies illustrating the use of TL for (i) energy prediction with mobility data and (ii) load forecasting in sports facilities are presented. Lastly, the paper ends with a discussion of the future directions.

Vulnerability assessment and federated intrusion detection of Air Taxi enabled smart cities

A Sustainable Smart City (SSC) has become the largest industrial sector that encompasses advanced cognitive, information, and computing methods for providing better big data handling to enhance the quality of life and urban operations with optimized resource utilization. Unmanned Aerial Vehicles (UAVs) are used as Air Taxis (ATs) in SSC, bypassing traffic congestion. However, the integration of ATs in SSC is very challenging, seeking high safety and security for the passengers. Such an autonomous system carries vital information, becoming vulnerable to furtive False Data Injection Attacks (FDIA), which have not received considerable research attention heretofore. To address the problem, this article establishes a model-free FDIA employing a recurrent deterministic policy gradient to exploit the data integrity of AT’s sensors, leading to collisions. Thereafter, a decentralized threat detection model, a deep optimized attentive federated aggregation learning is deployed, to counteract the threat and protect the data privacy of each AT. The suggested method is parallelizable and can accurately detect an unobservable FDIA in a distributed manner. The simulation findings show that the proposed attack–defense model investigates in-depth system’s vulnerabilities and tackles the risk with a higher detection rate and reduced computing cost while maintaining privacy preservation that surpasses modern approaches.