A Review on Integration of IoT as an Approach for Energy Saving in Smart Sustainable Cities

Rapid urbanization has been happening around the world,leading to many challenges and difficulties in infrastructure,communication network,transportation,environmental and organizational problems.Proper and responsible management of urban resources plays a significant role in sustainable development.Smart sustainable cities use ICTs(Information and Communication Technologies)to improve quality of life,efficiency of urban operation and services.The latest advancement in communication,technology,data management,and IoT(Internet of Things)provide a tremendous role for practical implementations and adoption of devices and entities.Smart sustainable cities can be intellectualized as an innovative approach of controlling urban resources and valuable components based on the latest advancement in ICT.Our study focuses on reviewing and discussing the literature that states the vital components of IoT associated with smart sustainable cities in general and specifically with green energy.

Understanding the Relationship Between Shrinking Cities and Land Prices:Spatial Pattern,Effectiveness,and Policy Implications

Urban shrinkage has emerged as a widespread phenomenon globally and has a significant impact on land,particularly in terms of land use and price.This study focuses on 2851 county-level cities in China in 2005–2018(excluding Hong Kong,Macao,Taiwan,and‘no data’areas in Qinhai-Tibet Plateau)as the fundamental units of analysis.By employing nighttime light(NTL)data to identify shrinking cities,the propensity score matching(PSM)model was used to quantitatively examine the impact of shrinking cities on land prices,and evaluate the magnitude of this influence.The findings demonstrate the following:1)there were 613 shrinking cities in China,with moderate shrinkage being the most prevalent and severe shrinkage being the least.2)Regional disparities are evident in the spatial distribution of shrinking cities,especially in areas with diverse terrain.3)The spatial pattern of land price exhibits a significant correlated to the economic and administrative levels.4)Shrinking cities significantly negatively impact on the overall land price(ATT=–0.1241,P<0.05).However,the extent of the effect varies significantly among different spatial regions.This study contributes novel insights into the investigation of land prices and shrinking cities,ultimately serving as a foundation for government efforts to promote the sustainable development of urban areas.

A Study on the Symbol-Based Narrative in the International Communication of Cities

Cultural symbols,a manifestation of cities’cultural resources,are not only signs that frame concepts but also forms that express meanings.Exploring the international communication of cities from the perspective of symbols,this paper analyzes in depth how cities create their cultural symbols in the dynamic process of international communication in an era of symbol-based digital media,and how they develop their narratives and explain meanings through the dissemination of symbols when telling their stories to international audiences,thus enhancing the efficiency and effectiveness of their international communication efforts.

A robust method for evaluating the potentials of 15-minute cities:Implications for sustainable urban futures

The‘15-minute city’(15minC)concept,which aspires to bring essential services within reach via a 15-minute walk for all residents,represents a pivotal paradigm shift in sustainable urban development.However,the achievability of this concept for different cities varies considerably across diverse population distributions,urban contexts,and development priorities.In this study,we propose a robust method for evaluating a city’s 15minC potential-a city’s capability to achieve widespread 15-minute accessibility while maintaining an optimal balance between resource efficiency and resident accessibility.We employ the Location Set Covering Problem optimization model to analyze the resources required to achieve full coverage of 15-minute accessibility and the knee point detection algorithm to assess a city’s 15minC potential.Across 23 major Chinese cities,our method exhibits a sharp sensitivity to delineate distinct 15minC potentials.It reveals that cities’current 15minC development level doesn’t align with their inherent potential uniformly.Key determinants include how well current facility locations match population centers and the population density in remote areas.Further,reducing facility constructions by twothirds has only a marginal impact on accessibility,emphasizing the need for tailored,data-driven planning in effective and sustainable urban development based on the distinct potentials of cities.Our approach prioritizes resource efficiency,minimizing the inefficient use of facilities that serve only a small portion of residents while maximizing the benefits of the 15minC and therefore has significant implications for a sustainable urban future.

Cyber Security within Smart Cities:A Comprehensive Study and a Novel Intrusion Detection-Based Approach

The expansion of smart cities,facilitated by digital communications,has resulted in an enhancement of the quality of life and satisfaction among residents.The Internet of Things(IoT)continually generates vast amounts of data,which is subsequently analyzed to offer services to residents.The growth and development of IoT have given rise to a new paradigm.A smart city possesses the ability to consistently monitor and utilize the physical environment,providing intelligent services such as energy,transportation,healthcare,and entertainment for both residents and visitors.Research on the security and privacy of smart cities is increasingly prevalent.These studies highlight the cybersecurity risks and the challenges faced by smart city infrastructure in handling and managing personal data.To effectively uphold individuals’security and privacy,developers of smart cities must earn the trust of the public.In this article,we delve into the realms of privacy and security within smart city applications.Our comprehensive study commences by introducing architecture and various applications tailored to smart cities.Then,concerns surrounding security and privacy within these applications are thoroughly explored subsequently.Following that,we delve into several research endeavors dedicated to addressing security and privacy issues within smart city applications.Finally,we emphasize our methodology and present a case study illustrating privacy and security in smart city contexts.Our proposal consists of defining an Artificial Intelligence(AI)based framework that allows:Thoroughly documenting penetration attempts and cyberattacks;promptly detecting any deviations from security standards;monitoring malicious behaviors and accurately tracing their sources;and establishing strong controls to effectively repel and prevent such threats.Experimental results using the Edge-IIoTset(Edge Industrial Internet of Things Security Evaluation Test)dataset demonstrated good accuracy.They were compared to related state-of-theart works,which highlight the relevance of our proposal.

Enhanced Cooling Efficiency of Urban Trees on Hotter Summer Days in 70 Cities of China

Increasing the urban tree cover percentage(TCP) is widely recognized as an efficient way to mitigate the urban heat island effect. The cooling efficiency of urban trees can be either enhanced or attenuated on hotter days, depending on the physiological response of urban trees to rising ambient temperature. However, the response of urban trees' cooling efficiency to rising urban temperature remains poorly quantified for China's cities. In this study, we quantify the response of urban trees' cooling efficiency to rising urban temperature at noontime [~1330 LT(local time), LT=UTC+8] in 17summers(June, July, and August) from 2003–19 in 70 economically developed cities of China based on satellite observations. The results show that urban trees have stronger cooling efficiency with increasing temperature, suggesting additional cooling benefits provided by urban trees on hotter days. The enhanced cooling efficiency values of urban trees range from 0.002 to 0.055℃ %-1 per 1℃ increase in temperature across the selected cities, with larger values for the lowTCP-level cities. The response is also regulated by background temperature and precipitation, as the additional cooling benefit tends to be larger in warmer and wetter cities at the same TCP level. The positive response of urban trees' cooling efficiency to rising urban temperature is explained mainly by the stronger evapotranspiration of urban trees on hotter days.These results have important implications for alleviating urban heat risk by utilizing urban trees, particularly considering that extreme hot days are becoming more frequent in cities under global warming.

Do companies influenced by smart cities pay more attention to green governance?Mechanism and optimal spatial correlation

Smart cities are a way for China to construct an innovative and environmentally conscious nation.The paper examines the impact of smart cities on corporate green governance and provides a theoretical foundation for formulating and executing smart city policy in China.Based on panel data from Chinese A-share listed companies in Shanghai and Shenzhen from 2008 to 2020,this study constructs a multiperiod double-difference model to examine the influence of smart cities on corporate green governance.Additionally,it uses a spatial double-difference model to investigate the spatial spillover effect of smart cities on neighboring areas.The findings indicate that smart cities effectively enhance corporate green governance.Analyzing the influencing mechanisms reveals that resource allocation efficiency,technological innovation,management environmental awareness,and regional environmental enforcement efforts act as mediators.Furthermore,the study reveals that the impact of smart cities on promoting corporate green governance is more pronounced in regions with lower levels of marketization and resource-based cities.Moreover,the research explores the spatial spillover effects of smart cities,with an effective radius of approximately 350 km.The optimal spatial correlation zone for green governance of businesses in neighboring areas in relation to smart cities is within a range of 250-350 km.This is manifested by the significant promotion of green governance in neighboring area businesses facilitated by smart cities.

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

Soundscapes in Arab Cities:A Systematic Review and Research Agenda

In the context of Arab cities,this study explores the intricate interplay between cultural,historical,and environmental elements that shape their unique soundscapes.The paper aims to shed light on this underrepresented field of study by employing a three-fold research approach:systematic review,a comprehensive literature review,and the formulation of a future research agenda.The first part of the investigation focuses on research productivity in the Arab world regarding soundscape studies.An analysis of publication trends reveals that soundscape research in Arab cities is still an emerging area of interest.Critical gaps in the existing body of literature are identified,highlighting the importance of addressing these gaps within the broader context of global soundscape research.The second part of the study delves into the distinctive features that inform the soundscapes of Arab cities.These features are categorized into three overarching groups:(i)cultural and religious life,(ii)daily life,and(iii)heritage and history,by exploring these factors,the study aims to elucidate the multifaceted nature of Arab urban soundscapes.From the resonating calls to prayer and the vibrant ambiance of traditional cafes to the bustling markets and architectural characteristics,each factor contributes to the auditory tapestry that defines Arab cities.The paper concludes with a forward-looking research agenda,proposing sixteen key questions organized into descriptive and comparative categories.These questions emphasize the need for a more profound understanding of sound perception,sources,and the impact of urban morphology on the soundscape.Additionally,they highlight the need for interdisciplinary research,involving fields such as urban planning,architecture,psychology,sociology,and cultural studies to unravel the complexity of Arab urban soundscapes.

Ensemble Deep Learning Based Air Pollution Prediction for Sustainable Smart Cities

Big data and information and communication technologies can be important to the effectiveness of smart cities.Based on the maximal attention on smart city sustainability,developing data-driven smart cities is newly obtained attention as a vital technology for addressing sustainability problems.Real-time monitoring of pollution allows local authorities to analyze the present traffic condition of cities and make decisions.Relating to air pollution occurs a main environmental problem in smart city environments.The effect of the deep learning(DL)approach quickly increased and penetrated almost every domain,comprising air pollution forecast.Therefore,this article develops a new Coot Optimization Algorithm with an Ensemble Deep Learning based Air Pollution Prediction(COAEDL-APP)system for Sustainable Smart Cities.The projected COAEDL-APP algorithm accurately forecasts the presence of air quality in the sustainable smart city environment.To achieve this,the COAEDL-APP technique initially performs a linear scaling normalization(LSN)approach to pre-process the input data.For air quality prediction,an ensemble of three DL models has been involved,namely autoencoder(AE),long short-term memory(LSTM),and deep belief network(DBN).Furthermore,the COA-based hyperparameter tuning procedure can be designed to adjust the hyperparameter values of the DL models.The simulation outcome of the COAEDL-APP algorithm was tested on the air quality database,and the outcomes stated the improved performance of the COAEDL-APP algorithm over other existing systems with maximum accuracy of 98.34%.

A learning automata based edge resource allocation approach for IoT-enabled smart cities

The development of the Internet of Things(IoT)technology is leading to a new era of smart applications such as smart transportation,buildings,and smart homes.Moreover,these applications act as the building blocks of IoT-enabled smart cities.The high volume and high velocity of data generated by various smart city applications are sent to flexible and efficient cloud computing resources for processing.However,there is a high computation latency due to the presence of a remote cloud server.Edge computing,which brings the computation close to the data source is introduced to overcome this problem.In an IoT-enabled smart city environment,one of the main concerns is to consume the least amount of energy while executing tasks that satisfy the delay constraint.An efficient resource allocation at the edge is helpful to address this issue.In this paper,an energy and delay minimization problem in a smart city environment is formulated as a bi-objective edge resource allocation problem.First,we presented a three-layer network architecture for IoT-enabled smart cities.Then,we designed a learning automata-based edge resource allocation approach considering the three-layer network architecture to solve the said bi-objective minimization problem.Learning Automata(LA)is a reinforcement-based adaptive decision-maker that helps to find the best task and edge resource mapping.An extensive set of simulations is performed to demonstrate the applicability and effectiveness of the LA-based approach in the IoT-enabled smart city environment.

Defining Cities by Water: Addressing Capital Misallocation in a Race to Conserve Resources

As part of its efforts to promote a sustainable and high-quality development,China has pledged to reduce water consumption and create a water-efficient society.On the basis of identifying the institutional root causes of excessive capital allocation and excessive water consumption in China’s water-intensive industrial sectors,this study elaborates how the national water-efficient cities assessment contributes to optimized capital allocation.Our research shows that national water-efficient cities assessment has motivated local governments to compete for water efficiency.To conserve water,local governments regulated the entry and exit of water-intensive enterprises,discouraged excessive investments in water-intensive sectors,and phased out obsolete water-intensive capacities within their jurisdictions.This approach has resulted in mutually beneficial outcomes,including improved allocation of capital,enhanced water efficiency,and reduced emissions.This paper offers policy recommendations for establishing a water-efficient society throughout the 14^(th) Five-Year Plan(2021-2025)period by presenting empirical evidence on the policy effects of resource efficiency evaluation.

Commuting Space of Primary and Secondary Schools in the Context of Child Friendly Cities:A Case Study of Bajiao Street of Shijingshan District

With the continuous promotion of the construction of child friendly cities,the school commuting space is an important component of the construction of child friendly roads.Based on the background of child friendly cities,the commuting space of 11 primary and secondary schools in Bajiao Street is analyzed through literature analysis and field research methods.Firstly,the relevant literature on school commuting space is sorted out,and the characteristics of school commuting space are summarized,including transportation,landscape,culture,leisure,and security.Secondly,the characteristics of commuting space of primary and secondary schools in Bajiao Street are analyzed from three aspects:in front of the school gate,path space,and node space.This paper aims to provide reference and guidance for the future construction of children’s walking school commuting and promote the construction of a child friendly city.

Impact of coupling coordination development of port and city environments on urban economic competitiveness:Evidence from the coastal port cities in eastern China

Promoting the coupling coordination development of port and its hinterland city environments is an important way to improve urban economic competitiveness.Based on relevant data of 13 coastal port cities in eastern China from 2000 to 2018,this study explores the coupling coordination development of port and city environments and its impact on urban economic competitiveness by constructing the coupling coordination degree model and the panel threshold model.The research results show that:(1)In terms of the coupling coordination development of port and city environments,most coastal ports and their hinterland cities are in a state of moderate or serious disorder.Overall,the degree of coupling coordination of port and city environments needs to be further improved;(2)The coupling coordination degree of port and city environments has a significant impact on urban economic competitiveness,and this effect gradually increases with the development of the ports and the urban economy.Among the variables that impact the urban economic competitiveness,fixed assets investment and foreign trade are significant factors that can enhance urban economic competitiveness.(3)At present,there is a“U-shaped”relationship between the coupling coordination degree of port-city environments and the urban economic competitiveness.This relationship lies on the right side of the inflection point of the“U-shaped”curve.Therefore,following the concept of assigning priority to ecological development,expanding fixed assets investment and actively developing foreign trade can further enhance the urban economic competitiveness.

Influence of Lightning Disaster on Cities and Lightning Defense Measures

Under the influence of special terrain and climatic conditions,lightning weather in Ulanqab City is more frequent from June to August,and lightning disaster has become one of the important tasks of disaster prevention and mitigation.In this paper,based on the characteristics of lightning weather in Ulanqab City,the impact of lightning disaster on the city was analyzed,and lightning protection measures,such as strengthening supervision of lightning protection safety,establishing a long-term lightning protection mechanism,doing a good job in lightning protection construction and detection in key places,and further improving public awareness of lightning protection,were put forward to reduce and avoid urban lightning disasters as much as possible and ensure urban safety.

Green transformation paths of resource-based cities in China from the configuration perspective

Green transformation is an unavoidable choice for resource-based cities(RBCs)that face resource depletion and environmental pollution.Existing research has focused primarily on specific RBCs,making it challenging to apply green transformation strategies universally across cities.The fuzzy set qualitative comparative analysis(fsQCA)is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome.Thus,to address this gap,in this study,we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China.By incorporating the element of time,this study explored the dynamic evolution of solutions in 2013,2016,and 2019.The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency(GTE),and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs.Green transformation paths of RBCs exhibit the same destination through different paths.Additionally,the combination of system environment elements and system structure elements is both complementary and alternative.Differences in RBCs have led to various factor combinations and development paths,but there are some similarities in the key elements of the factor combinations at different stages.Economic environment,government support,and technological innovation are key factors that universally enhance the GTE in RBCs.These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.

Application Strategies of Spatial Refinement Design in Ancient Cities Supported by Digital Te-Zhaoyu Ancient City in Qixian County as an Example

Digital technology provides a method of quantitative investigation and data analysis for contemporary landscape spatial analysis,and related research is moving from image recognition to digital algorithmic analysis,providing a more scientific and macroscopic way of research.The key to refinement design is to refine the spatial design process and the spatial improvement strategy system.Taking the ancient city of Zhaoyu in Qixian County,Shanxi Province as an example,(1)based on obtaining the integrated data of the ancient city through the drone tilt photography,the style and landscape of the ancient city are modeled;(2)the point cloud data with spatial information is imported into the point cloud analysis platform and the data analysis is carried out from the overall macroscopic style of the ancient city to the refinement level,which results in the formation of a more intuitive landscape design scheme,thus improving the precision and practicability of the landscape design;(3)Based on spatial big data,it starts from the spatial aggregation level,spatial distribution characteristics and other evaluation index system to achieve the refinement analysis of the site.Digital technology and methods are used throughout the process to explore the refined design path.

Leveraging AI for Energy-Efficient Smart Cities: Architectural and Urban Planning Solutions for Sustainable Growth - A Comparative Case Study of Amman City and International Examples

As cities worldwide face increasing energy demands and environmental sustainability challenges,the need for innovative solutions becomes more urgent.Smart cities,driven by advances in Artificial Intelligence(AI),offer promising avenues for enhancing energy efficiency,optimizing urban planning,and improving overall urban living conditions.This research explores how AI can be leveraged to develop energy-efficient smart cities by focusing on architectural and urban planning solutions that promote sustainable growth.The study includes a comprehensive literature review on the role of AI in managing energy consumption,optimizing transportation systems,and aiding urban planning efforts.A critical component of this research is the comparative analysis of case studies from both Jordan and international cities,such as Singapore,Barcelona,and Copenhagen,to evaluate the potential of AI-driven solutions in local contexts.This paper presents a case study applying an AI-driven smart city model to Amman,Jordan,where the city's urban infrastructure,energy management,and transportation systems are analyzed using AI-powered simulations.By integrating real-time data from IoT devices,geographic information systems(GIS),and digital twin technologies,the study simulates energy-saving interventions,improved traffic flow,and optimized urban designs.The research also compares the outcomes from Jordanian developments like Abdali Boulevard and Saraya Aqaba with international examples,revealing valuable insights into the progress and challenges of implementing smart city solutions in Jordan.Key outcomes include a reduction in energy consumption,carbon emissions,traffic congestion,and overall cost savings,demonstrating how AI can contribute to the sustainable development of modern cities.The findings from the case study provide a framework for the application of AI in other urban environments facing similar sustainability challenges,with a focus on enhancing local policy frameworks,infrastructure,and capacity to enable the successful integration of AI solutions.

Landslide-oriented disaster resilience evaluation in mountainous cities: A case study in Chongqing, China

Natural and human-made disasters are threatening cities around the world.The resilience of cities plays a critical role in disaster risk response and post-disaster recovery.In mountainous cities,landslides are among the most frequent and destructive hazards.This study presents a novel methodological framework for assessing the spatial resilience of mountainous cities specifically against landslides.Focusing on Chongqing in the Three Gorges Reservoir region,this study conceptually divides the disaster resilience of mountain cities to landslides into two dimensions:environmental resilience and social resilience.This study developed a comprehensive database by compiling data from 4,464 historical landslide events,incorporating 17 environmental resilience indicators and 16 social resilience indicators.Random forest(RF)model was employed to evaluate environmental resilience,achieving a high AUC of 0.968 and an accuracy of 97.1%.Social resilience was assessed by the Analytic Hierarchy Process(AHP),and comprehensive resilience was ranked by the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).Key findings include:(1)Establishing a multi-dimensional resilience indicator system that effectively assesses landslide-oriented resilience in mountainous cities.(2)Comprehensive resilience in mountainous cities exhibit distinct spatial clustering patterns.Regions with lower environmental resilience are mainly characterized by high rainfall and complex terrain.higher social resilience concentrated in city centers,while peripheral regions face challenges due to weaker economies and inadequate healthcare infrastructure.(3)In the future development of mountain cities,comprehensive and sustainable strategies should be adopted to balance the relationship between environmental resilience and social resilience.This study provides a robust framework for disaster prevention and resilience assessment in mountainous cities,which can be applied to evaluate the disaster resistance capabilities of other mountainous cities.

Comparative Study of Evaluation Indicators for Learning Cities and the Implications

With the development of society,more and more cities are participating in the initiative to build learning cities.Constructing an evaluation indicator system for learning cities to monitor the progress and promote their growth has become increasingly important.This paper analyzes the preliminary framework of the UNESCO Global Learning City Index and R3L+Quality Framework.The comparison is made from the aspects of design philosophy,criteria of indicator,and the cycle of evaluation process.The findings suggest that the construction of an evaluation indicator system should be focused more on the diversity of learning city development,the construction of an evaluation process cycle,and the significance of building cooperative networks.