Smart Sustainable Cities Research Articles

Transformation Model towards Sustainable Smart Cities: Riyadh, Saudi Arabia as a Case Study

The purpose of this research was to create a model that contributes to the transformation of Riyadh into a sustainable smart city, as well as to assess the extent to which Riyadh meets the requirements of smart cities in light of the proposed model. To achieve the study’s objectives, the descriptive survey method was used, with a questionnaire that included (30) items to collect appropriate data from the study sample, which consisted of (400) specialists in the field of smart sustainable cities. The study’s findings revealed that the model for transforming Riyadh into a smart sustainable city is built on a number of components, including sustainable urbanization patterns, urban systems and domains, data sources and storage services, cloud computing, big data applications and services, and urban communities and their activities. The study’s findings also revealed that the developed model’s contribution to the transformation of Riyadh into a smart sustainable city was significant, as the arithmetic mean of the respondents’ responses to the components of the study model as a whole was high (3.85). Based on these findings, the study recommended that the city of Riyadh review the urban patterns of modern residential neighborhoods and increase their environmental efficiency, as well as expand the establishment of urban observatories that deal with urban and environmental affairs and emphasize their role in the interim review of residential neighborhoods, which supports the city’s urbanization path. The study also recommended that the city of Riyadh develop and build massive data centers distributed across several regions, as well as work to enable the use of renewable energy production sources, in addition to consolidating Riyadh’s role as a regional center for cloud computing and an attractive technology investment based on innovation in the region.

Blockchain Meets Edge Intelligence for Smart Cities Sustainability: An Insightful Review and Prospective Analysis

The convergence of blockchain technology and edge intelligence has emerged as a transformative force in the realm of smart cities, offering unprecedented opportunities to enhance sustainability. This paper presents a comprehensive review and prospective analysis of this convergence, shedding light on its potential to revolutionize urban environments. We commence with an exploration of the fundamental components of blockchain technology, emphasizing its core principles of decentralization, immutability, and consensus mechanisms. Simultaneously, we trace the historical evolution of blockchain from its origins with Bitcoin to its broad applications in diverse domains. In the context of edge intelligence, we examine how this paradigm shift decentralizes data processing, enabling real-time decision-making and enhancing data security. We elucidate its key components, such as edge devices and analytics algorithms, while highlighting its critical role in reshaping the urban landscape. The crux of this paper lies in the convergence of blockchain and edge intelligence, where we explore its profound implications for the sustainability of smart cities. From efficient energy management and waste reduction to improved transportation and green infrastructure, this convergence empowers smart cities to optimize resource usage, reduce environmental impact, and enhance the quality of life for their residents. Through a prospective analysis, we anticipate emerging trends and innovations that will shape the future of smart city sustainability, including AI integration, 5G connectivity, and circular economy initiatives. As smart cities continue to evolve, they stand at the forefront of addressing urbanization challenges while fostering sustainable, inclusive, and prosperous urban environments.

Smart solid waste management solution Case study: East Mansoura district

Recently, the transformation of existing cities into smart cities has become an urgent necessity to solve urban problems by linking the dimensions of sustainability with information and communication technology to enhance the quality of life. The current research problem lies in the rapid increase in urban population growth, the increase in resource consumption over the past few decades, and the increase in migration rates from the countryside and neighboring villages to urban cities, which lead to an increase in the problem of solid waste management. Conventional waste management systems are not equipped to handle the excess waste generated by a growing population. To help bridge the gap, societies need to adopt smart waste management solutions that increase efficiency and reduce collection costs. Hence, transforming the solid waste management system into a Smart solid waste management system has become an urgent need for solid waste collection and treatment to achieve the Sustainable Development Goals (SDGs), especially in developing countries. Therefore, the study adopts examining the performance of East Mansoura city as a case study in the field of solid waste collection and treatment. To achieve the objective of this study, the key performance indicators for smart sustainable cities KPIs for SSC that were developed by the ITU and related to the collection and treatment of solid waste were adopted to measure and evaluate the current situation for the selected case study. Finally, an action plan was proposed to transform the waste management system in East Mansoura into a smart waste management system.

Visual Analytics and Digital Twin Modeling Tools, Spatio-Temporal Fusion and Predictive Modeling Algorithms, and Deep Learning-based Sensing and Image Recognition Technologies in Data-driven Smart Sustainable Cities and Immersive Multisensory Virtual Spaces

Visual Analytics and Digital Twin Modeling Tools, Spatio-Temporal Fusion and Predictive Modeling Algorithms, and Deep Learning-based Sensing and Image Recognition Technologies in Data-driven Smart Sustainable Cities and Immersive Multisensory Virtual Spaces

Enabling smart contributions for sustainable urban development

Urbanization as a global tendency continuously imposes an issue about smart solutions that make life comfortable , safe and environmentally friendly in cities. It is a challenge to transform a city into a smart and sustainable, with the aim to be adaptive enough to address the challenges of the future and to react to innovative or unexpected developments. Smart sustainable city concept is still evolving and meets with different perceptions of technological, environmental, economic and social relations. Therefore, this paper aims to deliver possible basis for the functioning of a smart and sustainable city in the so-called "smartization" process. Smart technologies that asses, monitor and manage data and processes in space are widely discussed. This research is based on a holistic approach in order to show that a successful transformation with clear progress can be achieved by implementing smart technologies with sustainable monitoring process and by integrating the main stake-holders to make the path to smartness successful for all people involved. In that manner cities are accelerating their transformation towards sustainable objectives, creating cleaner, cooperative places which fosters use of resources more efficiently and is flexible to future changes and innovations.

Residents’ awareness and knowledge of sustainable smart cities

Sustainable and smart city studies are issues that local governments, business circles, and the academic community often deal with regarding city and neighborhood developments. Various grant calls and research studies on the subject are frequently made, and its importance in the professional field is increasing. However, in these studies, where the society stands is often questioned. In addition, consumers and users are critical to realizing a sustainable and energy-efficient world. These users and consumers can be defined as an urban society in cities. Awareness, knowledge, and participation of city residents about sustainable and smart cities will play a significant role in the city’s journey to be sustainable and smart. In other words, increasing society’s awareness of sustainability will change attitudes and habits and make the city’s structure more sustainable and smarter. In this study, A 28-question survey was conducted with 518 participants on the society’s perspective and knowledge of sustainable smart urban areas. It was found that the participants had general knowledge and awareness of sustainability. However, they had partial and little knowledge about sustainable urban development and smart city practices, and only 15.31% of the participants knew all the terms such as sustainable environment, sustainable society, and smart life related to these concepts. While some of the results are compatible with each other, many of them are contradictory. Different studies can be done based on these contradictions.

Determination Factors of Roadside Tree Species Selection Model for Sustainable Smart City

This study aimed to determine the factors that are essential in developing Malaysian Roadside tree selection species model for a sustainable smart city. Two objectives have been formulated; (i) to identify the current practices in selecting roadside trees and (ii) to explore the factors affecting in developing roadside tree species model. The methodology used in the study is in-depth interviews and collecting archival data. Thirty of landscape architects and related expertise will be sorted by random sampling at Klang Valley area. The study emphasised the consideration of landscape, arboriculture, forestry and academician practices that consider the long-term benefits and impacts of planting roadside trees. The findings of this study provide valuable insights into the factors that should be considered when selecting tree species for roadside planting in city areas. Fifteen (15) important factors has been identified that is size and growth habit, native and local species, adaptability, maintenance and requirements, wind resistance, non-invasive roots, canopy density, soil requirements, aesthetic value, wildlife support, cultural significance, stakeholder input, longevity, urban tolerance, pest and disease resistance. The results can be used to guide the related parties and promote sustainable development in cities.

Direction for a Transition toward Smart Sustainable Cities based on the Diagnosis of Smart City Plans

Achieving urban sustainability through smart cities is necessary to manage urban environmental problems that threaten human survival. Smart city policy emphasizes the environmental aspects of urban areas while embracing the social and economic sectors, allowing for the development of practical plans for urban sustainability. This study suggests smart sustainable city policy directions that can improve the transition to smart cities. It defines concepts such as smart sustainable cities, developing frameworks, and indicators. In this research, a smart sustainable city facilitated sustainable development by incorporating smart technologies into urban activities and services. In this study, indicators for smart sustainable city evaluation and diagnosis were derived. These were applied to selected case areas, such as Incheon Metropolitan City and Goyang-si, Gyeonggi-do in the Republic of Korea. These indicators play an important role in assisting policymakers in making decisions, simplifying a wide range of complex information and providing integrated perspectives on existing situations. The results of this study suggest transition directions for a smart sustainable city and application strategies for related plans and policies.

빅데이터 기반의 도시정보·대중교통 접근성 분석 플랫폼 구축 방안에 관한 연구

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the “Big Data” environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

Achieving Sustainability in Smart Cities & Its Impact on Citizen

Life became digitalized and smartly controlled that requiring more energy usage. Smart cities and urbanization focus on the challenge of worldwide urbanization through the recognition of opportunities to integrate social, physical, environmental and technological infrastructure. Urbanization expands the need of all services including water, power, transportation, as well as other facilities. All those infrastructures should be delivered to citizen within a short period of time with very well controlled systems to provide more simple and comfortable life. Furthermore, stakeholders and citizens should be responsible and cooperative with government and organizations in order to achieve better solution for smart sustainable living approach. Although the smart urbanization has the potential to become a positive transformative force for every aspect of sustainable development in cities, there is a lack of knowledge using the smart and sustainable concepts in cities. Therefore, this paper aims to propose a framework which merges the sustainable aspects with the Smart city components. The paper started by an analytical study about smart cities fields and their needs, then a study for sustainability aspects, all this end with a framework tested by a questionnaire to propose guidelines and recommendations to be followed by city planners in order to achieve sustainability goals in smart cities for better impact on citizens.

Modelling a Sustainable Smart City Based on Human and User Centred Design

A smart, sustainable city that employs ICTs (information and communication technologies) improves urban businesses and services’ quality of life, productivity, and competitiveness. A sustainable smart city’s significant challenges are legislation and regulations, financing, technical and infrastructural dimensions. While at the same time providing for the economic, social, environmentally, and cultural needs of the present and future generations. Continuous population and urban development have stepped up creative ways of tackling urbanization, with limited implications supporting smart cities’ environments. This cram aimed to build a user-centred design using a sustainable big data analytics assisted optimization framework (SBDAAO) to step up creative ways of tackling urbanization with limited environmental implications. This research represents a first move to provide perspectives and value in creating intelligent cities to instil sustainability. Simulation analysis has been carried out based on the data collected based on city infrastructure. The experimental results have been executed, and the suggested method achieves an accuracy ratio (98.2%), the efficiency ratio (95.5%), energy consumption (20.1%), average communication delay (17.6%), and renewable power (93.9 %).

An IoT based environment conscious green score meter towards smart sustainable cities

In today’s modern world, use of natural resources is expanding certainly because of the refined lifestyle of the individuals. The unjustifiable use of these non-renewable resources can affect the stability between environmental and biological diversity which leads to greenhouse effect. This situation requires awareness and motivation to encourage people towards sustainable energy use and conservation in order to reduce global warming. For effective implementation, government initiatives require a systematic public participation to assess household’s level of energy self-sustainability and reward accordingly. On this regard, we introduce an IoT powered green architecture to assign an optimal green score to a household by assessing the households’ level of energy self-sustainability using a novel green score algorithm based green score meter. The green score algorithm will results high green score rating to a household with high renewable energy production than the non-renewable energy consumption with less air contamination. Based the household energy data, the green score meter computes the green score rating of a household using the green score algorithm and forward the score to the authorized third party like cloud server for green rank calculation and virtual display. Here, we present a tax exemption scheme which benefits the households with high green score rating. The existing frameworks (HEMS, iCHEMS, SHEMS) monitor and aware the user/household for efficient energy management, cost management but in contrast our proposed green architecture is an integrated platform for collective energy management to evaluate energy self-sustainability of the household, so as to give financial incentives. Thus, our proposed green score based tax exemption scheme will appreciate and urge the residents to burn-through less natural assets and forestall less contamination.

Crop Type Prediction: A Statistical and Machine Learning Approach

Farmers’ ability to accurately anticipate crop type is critical to global food production and sustainable smart cities since timely decisions on imports and exports, based on precise forecasts, are crucial to the country’s food security. In India, agriculture and allied sectors constitute the country’s primary source of revenue. Seventy percent of the country’s rural residents are small or marginal agriculture producers. Cereal crops such as rice, wheat, and other pulses make up the bulk of India’s food supply. Regarding cultivation, climate and soil conditions play a vital role. Information is of utmost need in predicting which crop is best suited given the soil and climate. This paper provides a statistical look at the features and indicates the best crop type on the given features in an Indian smart city context. Machine learning algorithms like k-NN, SVM, RF, and GB trees are examined for crop-type prediction. Building an accurate crop forecast system required high accuracy, and the GB tree technique provided that. It outperforms all the classification algorithms with an accuracy of 99.11% and an F1-score of 99.20%.

Zero-Shot Video Grounding for Automatic Video Understanding in Sustainable Smart Cities

Automatic video understanding is a crucial piece of technology which promotes urban sustainability. Video grounding is a fundamental component of video understanding that has been evolving quickly in recent years, but its use is restricted due to the high labeling costs and typical performance limitations imposed by the pre-defined training dataset. In this paper, a novel atom-based zero-shot video grounding (AZVG) method is proposed to retrieve the segments in the video that correspond to a given input sentence. Although it is training-free, the performance of AZVG is competitive to the weakly supervised methods and better than unsupervised SOTA methods on the Charades-STA dataset. The method can support flexible queries as well as different video content. It can play an important role in a wider range of urban living applications.

Modelling a Sustainable Smart City

This article presents the development of a model of a sustainable smart city. The model demonstrates the use of sustainable forms of energy and incorporates Internet of Things functionalities to simulate energy efficiency, monitoring of air quality, and safety. The city was designed to raise awareness about problems people living in cities face, as well as to inspire relevant technology-based innovative solutions in the context of the Sustainable Development Goal 11 (Sustainable Cities and Communities).

Smart sustainable cities: synergies between circular economy, innovative policies and European projects

Abstract: Metropolitan cities trying to respond to a locally-embedded global challenge: to implement a sustainable use of natural resources in order to avoid potential dramatic environmental scenarios. Metropolitan Cities could become a front-runner city in this field, if it demonstrates to be able to support its existing adaptive and transformative governance capacities. The goals and results achieved in the on-going Metropolitan City EU funded projects are described as “soft” policy tools for describing the thesis argued in the paper. Circular Economy, Green Economy (Green growth) and Bio economy have a common finalistic aspect: find a common ground for both economic, environmental and social goals. The Metropolitan Strategic Plan could represent a significant model for other Public Bodies. Indeed, this case study aims at demonstrating how strategic lines of intervention in trans-sectorial policies may be identified, such as for instance those related to the development of Circular Economy. The borders of Metropolitan cities functional urban area bound all the paper findings. The political recommendations stated represent an inspiring case study on how economic development can materialize in vision-oriented and strategically planned interventions.

An evaluation of stakeholders' participation process in developing smart sustainable cities in Saudi Arabia

PurposeThe smart sustainable cities (SSC) concept has a wide acknowledgement amongst governments and societies that deal with emerging technology and help in developing better urban communities. However, the fact that citizens' participation (CP) is not adherent to the current policies and governance often boosts their aspirations of decision-making to become smart cities. This paper aims to identify SSC variables and, more importantly, rank, categorise and discuss the factors towards implementing SSC by engaging, empowering and enabling citizens to participate in the urban development of SSC.Design/methodology/approachA comprehensive literature review identified 38 factors in the CP process. Those factors were used to design an online questionnaire administered to the respondents. A total of 164 valid responses were collected. A two-stage statistical analysis was adopted. First, the Relative Importance Index (RII) was used to rank and prioritise the importance of the factors that affect the current policies and agenda. Second, factor analysis was utilised to categorise and group those factors.FindingsThis study founds four significant factors that help in implanting SSC: “knowledge of smart sustainable cities”, “awareness of smart sustainable cities”, “willingness of the citizens to participate” and “opinion on the current agenda of the government's role”.Research limitations/implicationsThis study has a few limitations which can be considered in future studies. First, the response rate of the participant is relatively low (163), so sampling a larger segment will support the broader perception of the citizens.Practical implicationsThe outcome of this paper underlines the need for the successful implementation of smart cities by adopting CP in the process of impacting policies and governance. Particularly, it identifies factors that help cities and policymakers in engaging CP in developing new policies and revising existing policies for promoting SSC.Originality/valueThere is a need to investigate the most critical factors that influence CP for implementing SSC. These factors have not been adequately examined in extant literature.

The Impact of Stakeholders’ Management Measures on Citizens’ Participation Level in Implementing Smart Sustainable Cities

Smart sustainable cities (SSC) tend to utilise technology to promote themselves by involving their citizens in urban development. Several cities around the world have adopted the “smart city” label in recognition of these advantages. In fact, citizen engagement in public urban development and decision making has been acknowledged globally in many countries; yet, evaluations of the outcomes that allow the contribution of empowerment to be measured and compared with other influences are lacking. This study examines the correlation between stakeholder management measures (SMM) and citizen participation level (CPL) in the process of achieving an SSC. Four SMM factors were extracted from a literature review and sent out to be examined by experts in the field of built environments. Mean score (MS) ranking was used to confirm the importance of these variables in terms of predicting correlations with CPL. The results were generalised by multiple regression analysis techniques. This study shows a positive significant correlation between SMM and CPL in terms of Regulation, Collaboration, Legitimates, and Control. These four predictors make a significant contribution to escalating the levels of engagement and empowerment of citizen participation (CP). This paper contributes to knowledge in the field by identifying pillars that can increase CPL. Our findings could support the stakeholders of SSC projects to raise CPL, not only by hearing their voices but also by delegating power.

ISSUES AND WAY FORWARD FOR THE SMART SUSTAINABLE CITIES AND COMMUNITIES STANDARDS: THE MALAYSIAN CASE IN THE POST-COVID-19 ERA

Governing a city’s development with the use of standards started relatively recently, in the mid-2010s. However, the issues of such city standards in systematically governing future smart cities remains largely unknown under the digital infrastructural stress of the post-COVID-19 era. Therefore, this paper aims to examine the issues and directions in developing the Malaysian smart sustainable cities and communities standards that suit the post-COVID-19 era. This study applied the multiple case study method to compare the international literatures and the local smart city webinars. The results showed that smart city standards were welcomed by policymakers and practitioners, although issues such as learning, connectivity, and citizenship rationale need to be addressed. More focus should be put on how humans relearn and responsibly participate in the post-COVID-19 cyber-physical ecosystem in order to create a healthy and sustainable digital-based society. This paper has contributed as one of the first researches examining the role of smart city standards in Malaysia.

TESS: multivariate sensor time series prediction for building sustainable smart cities

Time series analysis can help build sustainable smart cities with high energy efficiency. Smart cities contain a large number of sensors. The sensor data are mostly complex time series, such as traffic, electricity, and gas emission data. Accurate time series prediction can greatly help reduce energy consumption and gas emission. It is difficult to make accurate time series prediction because there are complex correlations among time series and the data have local and global nonlinear dependencies. To overcome the difficulties, we first analyze state-of-the-art works of time series prediction. Then we propose a new framework for Time series prediction evaluation for Energy conServation and emission reduction in Smart cities, called TESS. TESS is used to compare the latest time series prediction models based on six publicly available datasets and three simulation datasets. Based on the theoretical analysis and the experiment result, we get some interesting ideas: time series in smart cities often have obvious periodicity and scale changes, and need to be collected over the long term; skip-connection is helpful for learning long-term features of time series; the recurrent layer is good at predicting time series with obvious periodicity; and linear regression may be more appropriate for predicting time series with scale changes.