Future Cities Research Articles

Contextual visual and motion salient fusion framework for action recognition in dark environments

Infrared (IR) human action recognition (AR) exhibits resilience against shifting illumination conditions, changes in appearance, and shadows. It has valuable applications in numerous areas of future sustainable and smart cities including robotics, intelligent systems, security, and transportation. However, current IR-based recognition approaches predominantly concentrate on spatial or local temporal information and often overlook the potential value of global temporal patterns. This oversight can lead to incomplete representations of body part movements and prevent accurate optimization of a network. Therefore, a contextual-motion coalescence network (CMCNet) is proposed that operates in a streamlined and end-to-end manner for robust action representation in darkness in a near-infrared (NIR) setting. Initially, data are preprocessed to separate foreground, normalized, and resized. The framework employs two parallel modules: the contextual visual features learning module (CVFLM) for local feature extraction, and the temporal optical flow learning module (TOFLM) for acquiring motion dynamics. These modules focus on action-relevant regions used shift window-based operations to ensure accurate interpretation of motion information. The coalescence block harmoniously integrates the contextual and motion features within a unified framework. Finally, the temporal decoder module discriminatively identifies the boundaries of the action sequence. This sequence of steps ensures the synergistic optimization of both CVFLM and TOFLM and thorough competent feature extraction for precise AR. Evaluations of CMCNet are carried out on publicly available datasets, InfAR and NTURGB-D, where superior performance is achieved. Our model yields the highest average precision of 89% and 85% on these datasets, respectively, representing an improvement of 2.25% (on InfAR) compared to conventional methods operating at spatial and optical flow levels which underscores its efficacy.

Delineating groundwater potential zones using integrated remote sensing and GIS in Lahore, Pakistan.

Groundwater depletion and water scarcity are pressing issues in water-limited regions worldwide, including Pakistan, where it ranks as the third-largest user of groundwater. Lahore, Pakistan, grapples with severe groundwater depletion due to factors like population growth and increased agricultural land use. This study aims to address the lack of comprehensive groundwater availability data in Lahore's semi-arid region by employing GIS techniques and remote sensing data. Various parameters, including Land Use and Land Cover (LULC), Rainfall, Drainage Density(DD), Water Depth, Soil Type, Slope, Population Density, Road Density, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-Up Index (NDBI), Moisture Stress Index (MSI), Water Vegetation Water Index (WVWI), and Land Surface Temperature (LST), are considered. Thematic layers of these parameters are assigned different weights based on previous literature, reclassified, and superimposed in weighted overlay tool to develop a groundwater potential zones index map for Lahore. The groundwater recharge potential zones are categorized into five classes: Extremely Bad, Bad, Mediocre, Good, and Extremely Good. The groundwater potential zone index (GWPZI) map of Lahore reveals that the majority falls within the Bad to Mediocre recharge potential zones, covering 33% and 28% of the total land area in Lahore, respectively. Additionally, 14% of the total area falls under the category of Extremely Bad recharge potential zones, while Good to Extremely Good areas cover 19% and 6%, respectively. By providing policymakers and water supply authorities with valuable insights, this study underscores the significance of GIS techniques in groundwater management. Implementing the findings can aid in addressing Lahore's groundwater challenges and formulating sustainable water management strategies for the city's future.

Enhancing Agricultural Practices through ICT: The Diffusion and Impact of the Among Tani Application in Batu City, Indonesia

This study examines the implementation and impact of the Among Tani application, a digital platform designed to support farmers in Batu City, Indonesia, as part of a broader smart city initiative. Utilizing a qualitative approach, the research investigates the diffusion process of the application, its role as a virtual communication medium, and its effects on organizational structures within farmer groups. The study reveals a staged adoption process influenced by factors such as farmer age and crop vulnerability. While the application has enhanced access to agricultural information and improved pest management, challenges including the digital divide and integration with traditional practices persist. The findings highlight the complex interplay between digital innovation and existing agricultural systems, emphasizing the need for context-sensitive approaches in implementing agricultural technologies. This research contributes to the understanding of digital agriculture's potential in supporting sustainable rural development and provides insights for future smart city initiatives in agricultural contexts.

미디어 빅데이터 의미연결망을 통해 본 문화도시와 관광 담론 연계: 공주 문화도시 사례

Purpose: This study is aim to make policy suggestions to secure sustainability in promoting Cultural City policies. Cities discover and reinterpret existing original to secure competitiveness, but cities can survive by creating new cultures. Tourism also contributes to the creation of economic effects by emphasizing industrial aspects, but essentially, tourism plays a role in enjoying the culture of the city and further creating a new culture. Nevertheless, culture and tourism tend to become instrumental and means of urban development, which will be set as a hurdle to sustainable urban development. Methods: The discourse that appeared in the media was analyzed targeting Gong-Ju City, Chung-Nam Province, which was recently designated as a Cultural City. For about 6 years from January 2018 to December 2023, big data on cultural cities and tourism mentioned on media reports and SNS were collected, and discourse was presented through frequent word frequency analysis, centrality analysis, and CONCOR analysis. For data collection, processing, and analysis, a big data solution, TEXTOM was used. Results: A total of 4,030 documents and 17,530 words with the keywords of Gong-Ju, Cultural City, and tourism were collected. In addition to the search keywords, tourism-related travel, tourist cities, and tourists accounted for the high frequency along with words such as culture, travel, Chung-Nam, hosting, and promotion. Centrality analysis revealed culture, city, tourism, region, and history are orient direction of discourse. As a result of the discourse analysis, the orientation of the future cultural city through history, the life-style resources of local residents as cultural resources, policies and programs activation before and after the designation of a cultural city, and the possibility of the tourism industry for a cultural city were extracted. Conclusion: Since Gongju, a Cultural City, was initial stage, there was a limit to discovering how it was connected to regional differentiation and tourism. However, it was suggested how to create a new discourse by linking tourism, focusing on the research results and developmental suggestions through previous studies.

지속가능한 도시로서의 스마트 도시재생을 위한 리질리언스 정책 방향에 관한 연구

The purpose of this study is to find Policy measures that can help smart cities contribute to urban regeneration as sustainable safe cities. This is a policy direction to move toward a sustainable city by combining smart cities and urban regeneration, which are spreading as models of future safe cities. After analyzing the trends of existing papers using text mining techniques, the concept of disaster resilience was grafted to smart city regeneration. The basic elements that constitute the qualitative criteria of resilience were used as the study method for building a sustainable city. Results, the policy direction of resilience construction for a ‘sustainable urban regeneration-type smart city’ was presented in three aspects. First, it’s constructing resilience capacity in smart urban regeneration plans. The qualitative criteria for resilience capacity were presented as four: Resourcefulness Robustness, Rapidity, and Redundancy. The four elements of disaster preparedness resilience capacity can be used as qualitative criteria for resilience required for smart urban regeneration as a safe city. The Second is the construction of the ‘decision support system for resilience’ that is needed for smart urban regeneration plans. For this, seven types of infrastructure were presented. These infrastructural interrelationships form the basis for the operation of the ‘decision support system for resilience’. Third, the establishment of ‘Privacy by Design as a smart resilience’ is necessary for the preemptive protection of personal information in smart urban regeneration. Privacy protection is essential for a modern safe city. In conclusion, we hope that the policy directions of the above three aspects will be linked to legislation and contribute to the activation of urban regeneration-type smart city as a sustainable and safe city in the future.

Freeing imagination for fair and resilient future cities

Freeing imagination for fair and resilient future cities

Backcasting Analysis of Autonomous Vehicle Implementation: A Systematic Review

The introduction of autonomous vehicles (AVs) has the potential to drastically change society, planning, design, and development strategies. This study uses the PRISMA protocol to carry out a systematic literature review, focusing on the backcasting method as an analytic tool. By examining. 21 studies published between 2003 and 2024, this paper highlights the phases of backcasting: visioning, policy packaging, and appraisal, and identifies critical factors necessary for the successful integration of AVs. Visioning for future driverless cities includes high-quality urban areas, active mobility, and innovative developments. Policies and Packaging suggested a focus on restricting vehicular access, transit-oriented development, and encouraging public transportation. Appraisal reveals skepticism about the positive impacts of AVs, urging policies that limit access to urban areas and promote sustainable modes of transportation. The main contribution of this study lies in its comprehensive application of backcasting to AV implementation, offering a structured approach to envisioning future urban scenarios, formulating supportive policies, and evaluating their impact. This analysis provides a solid foundation for future research, urging us to explore the intersection between AVs, citizen participation, and environmental sustainability to achieve more efficient and sustainable cities.

Fostering Sustainability Through Project-Based Learning: The Sustainable City Project, A Case Study in Primary Education

The Sustainable City Project aims to engage students in design and programming to construct dwellings that integrate creative and sustainable solutions. Utilising platforms like Tinkercad and Makecode to code the micro:bit, students work in teams to tackle urban challenges, proposing innovative solutions. This project promotes sustainability across various domains including energy efficiency, natural resource management, sustainable mobility and enhancing quality of life. Emphasising social inclusion and urban resilience, it seeks to build a more just and equitable future city. This research article explores the competencies developed, the methodology employed and the educational significance of the Sustainable City Project, highlighting its multidisciplinary approach at the intersection of technology, sustainability and creativity.

The new paradigm of future cities? Facilitating dialogues between the 15-minute city and the 15-minute life circle in China based on a bibliometric analysis

Cities worldwide are facing increasing disturbances due to the long-lasting COVID-19 pandemic, the unpredictable climate change, and the intensifying geopolitical clashes. The uncertainties associated with the future drive a backlash against contemporary planning practices that center on growth-oriented agenda and placemaking to survive neoliberal inter-city competitions. A noticeable paradigm shift towards micro-scale and human-centric planning practices has gained traction. The 15-minute city model (FMC), which was proposed by Carlos Moreno in 2016 and went viral after the pandemic, has become a prominent concept in steering future city development. Interestingly, China has also embarked on a transition from physical-oriented to human-centric planning, which is featured by the concept of the 15-minute life circle (FLC) and its planning guidelines first promulgated in Shanghai in 2016. While both concepts have thrived since then, few scholarly attempts have been made to advance the mutual learning process. This research aims to facilitate a dialogue between the two research communities, starting with a systematic literature review of the FMC. Using a bibliometric analysis, it maps the development and evolution of research on the FMC and identifies four key themes: sustainability, resilience, utopian city models, and technology. Based on the findings, the research discusses the complexity and current trends in the FMC literature. It compares the human-centric and chrono-urbanism planning principles in FMC and FLC cases, highlighting the differences in origins, priorities, and planning principles. The study concludes with three directions for mutual learning: integrating resilient thinking, synthesizing theoretical development and practical accumulation, and adopting a new urban regeneration perspective.

Changes in Land Use and Land Cover, Normalized Difference Vegetation Index and Land Surface Temperature in the Narsingdi District During 2001 to 2021

Rapid urbanization and industrialization cause land use changes, reduce green spaces, and increase the land surface temperature. Green spaces of a city area maintain environmental quality by absorbing air pollutants and reducing land surface temperature. The present study aimed to detect the changes in land use and land cover (LULC), normalized difference vegetation index (NDVI), and land surface temperature (LST) in the Narsingdi district including six Upazilas from 2001 to 2021. The Landsat 7- Enhanced Thematic Mapper Plus (ETM+), the Landsat 8- Operational Land Imager (OLI) imageries and the Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to analyze the LULC, NDVI, and LST by using Google Earth Engine (GEE) and ArcGIS 10.8.2. The images were analyzed into four land use classifications – agricultural land, built-up area, forest vegetation, and water body. Among all the Upazilas, Narsingdi Sadar was the vulnerable area, where agricultural land, forest coverage, and water body decreased significantly by 6.67%, 2.2%, and 4.66%, respectively. The built-up area increased by a considerable amount of 13.53% during the last twenty years. The forest coverage of Narsingdi Sadar Upazila was calculated at only 8.91% in 2021 and decreased from 11.11% in 2001. The NDVI values surprisingly increased in all the Upazilas, but in Narsingdi Sadar, it is comparatively low (0.08) than in other Upazilas. The increasing trend in LST in the Narsingdi Sadar Upazila is alarming, 1.14oC from 2001 to 2021 (0.57oC/decade). The significant changes in LULC, NDVI, and LST made the Narsingdi Sadar a more critical area in the Narsingdi district. The findings of the study will be helpful to policymakers in making appropriate decisions in future city development. J. of Sci. and Tech. Res. 5(1): 93-118, 2023

Seamless rate adaptation for wide SNR range in FSO systems based on rate compatible modulation.

We propose and experimentally demonstrate a large-range and seamless rate-adaptive free-space optical (FSO) scheme based on rate compatible modulation (RCM). It utilizes a mapping method through weighted summation, enabling an even increase of bit energy. This allows the system to seamlessly adjust the throughput. In addition, the handover mechanism based on rate check and acknowledgment signals ensures a wide coverage of signal-to-noise ratio (SNR) fluctuation. It is worth noting that this scheme does not require any changes to the mapping matrix and decoding algorithm, making it easier to implement in real-world systems. Simulation proves the superiority of the proposed approach in terms of coding rate coverage by applying a fixed mapping matrix compared to a traditional adaptive modulation and coding scheme. Experimental demonstration over a 50 m FSO link verifies that the SNR dynamic range of this scheme is >15 dB with a seamless rate adjustment between 6.7 Gb/s and 53.6 Gb/s and the operability of RCM is not limited by the time scale of turbulence, revealing huge potential for the massive connections in future smart cities.

Ecological benefits of roof gardens and the difference of roof gardens in different regions

As a result of the rapid pace of urbanization today, environmental destruction is outpacing regeneration, and many "urban diseases" are occurring frequently. Therefore, there is a need for a facility that can protect the environment without destroying the original city - roof gardens. This paper focuses on the ecological benefits of rooftop gardens and their application in practical situations. It is found that rooftop gardens can improve air quality, store rainwater, mitigate the heat island effect and protect biodiversity. These effects have well alleviated the problems of urban air pollution, water resource stress, urban heat island effect and destruction of ecological environment. And research has found that there are already many excellent examples of the application of rooftop gardens at home and abroad, helping to confirm that rooftop gardens do indeed have the ecological benefits mentioned above, adding to the feasibility. Rooftop gardens are indispensable in the construction of future cities for the well-being of urban residents.

The Paradox of Kowloon Walled City: Architectural Anomaly and Social Microcosm

Kowloon Walled City (KWC), formerly the world’s most densely populated place, is an example of urban density and self-organization in opposition to current urban developments, such as NEOM’s The Line, which illustrates the future of envisioned sustainable living. The main research question addressed in this study is: How can principles of self-organization and resilience from densely populated historical urban areas be applied to enhance the sustainability and livability of future planned urban developments? This study investigates the critical components of urban livability and governance amid severe densities by examining the underlying factors that lead to KWC’s unique sort of urban equilibrium and comparing them to the ideas that motivated the creation of The Line. This multidisciplinary research employs qualitative analysis to focus on architectural styles, community interactions, and governance systems. This approach allows for an in-depth examination of the parallels and dissimilarities between natural city evolution and future city planning. Key findings reveal that KWC’s functioning stems from its complex social fabric and adaptable informal governance, providing valuable lessons in resilience and community-driven urban development. The results suggest that the flexibility and community-driven efforts of KWC are essential for ensuring long-term viability, and these aspects may be integrated into contemporary projects such as The Line. The outcomes highlight the potential of combining KWC’s social cohesiveness with The Line’s technology developments to create urban environments that are both robust and sustainable. The results are supported by evidence obtained from historical analysis, which showcases the practical uses of integrating organic and planned urban development concepts.

Congestion Transition on Random Walks on Graphs.

The formation of congestion on an urban road network is a key issue for the development of sustainable mobility in future smart cities. In this work, we propose a reductionist approach by studying the stationary states of a simple transport model using a random process on a graph, where each node represents a location and the link weights give the transition rates to move from one node to another, representing the mobility demand. Each node has a maximum flow rate and a maximum load capacity, and we assume that the average incoming flow equals the outgoing flow. In the approximation of the single-step process, we are able to analytically characterize the traffic load distribution on the single nodes using a local maximum entropy principle. Our results explain how congested nodes emerge as the total traffic load increases, analogous to a percolation transition where the appearance of a congested node is an independent random event. However, using numerical simulations, we show that in the more realistic case of synchronous dynamics for the nodes, entropic forces introduce correlations among the node states and favor the clustering of empty and congested nodes. Our aim is to highlight the universal properties of congestion formation and, in particular, to understand the role of traffic load fluctuations as a possible precursor of congestion in a transport network.

How to Make Future Cities Smart in the Realm of Environmentally Friendly Healthy Cities? Looking from the Perspective of Ease of Living Index

Rapid urbanization and environmental issues have led the Government of India to implement urban development initiatives like Heritage City Development and Augmentation Yojana, Atal Mission for Rejuvenation and Urban Transformation, Smart Cities Mission, Deen Dayal Antyodaya Yojana-National Urban Livelihood Mission, and Swachh Bharat Mission-Urban to improve citizens' quality of life. The Ease of Living Index (EOL), developed to assess the outcomes of these initiatives, is a data-driven assessment tool aligned with the Sustainable Development Goals that enables cities to adopt evidence-based planning and execution. It assesses the well-being of citizens in 111 cities, including cities under the Smart Cities Mission, capital cities, and cities with populations over one million. The concept of healthy cities gained popularity in the South-east Asian Region of the World Health Organization, with the Healthy City Network Assessment Tool being introduced in 2021 to help cities assess their health profile in its eleven member countries, including India. In view of NITI Aayog's 2021 recommendation for the development of 500 healthy cities by 2030, there is a need to expand the scope of the existing EOL Index (2020). This research aims to integrate the healthy city evaluation criteria from WHO's South-east Asia Regional Guidelines with the EOL Index 2020 to develop an integrated tool for data-driven assessment of India's proposed healthy cities program. The study based on literature review and comparative analysis identifies 8 determinants, 28 sub-determinants and 112 indicators, enhancing the comprehensiveness of the EOL Index to promote smart, environmentally friendly, healthy, and sustainable urban development.

Planning and Development of Smart Cities Based on the Concept of Sustainable Development

Based on the idea of sustainable development, this paper explores the planning and development of smart cities. Cities face many issues as global urbanization picks up speed, including environmental pollution, resource depletion, traffic congestion, and social inequality. To address these challenges, the notion of sustainable development has become a guiding principle for many city policymakers, aiming to meet contemporary needs while safeguarding future development. Smart cities utilize advanced information and communication technology to enhance urban operational efficiency, improve resource management, and enhance residents' quality of life, thereby providing a more sustainable development model for cities. This paper focuses on the key areas of smart city planning, including energy utilization and environmental protection, smart transportation and urban mobility, smart city planning and land use, social equity, and community engagement. Using Shenzhen as a case study, the practical application of the notion of sustainable development in smart city construction is elucidated, providing valuable insights and practical references for future smart cities.

A fuzzy analytical hierarchy process -GIS approach to flood susceptibility mapping in NEOM, Saudi Arabia

The Kingdom of Saudi Arabia is undergoing massive and rapid urbanization as part of Vision 2030. This includes development projects along Saudi Arabia’s coastline across the Red Sea. Coastal areas, especially the ones along Saudi’s western regions are susceptible to natural disasters such as flooding. NEOM, a futuristic city currently being developed in the northwest of Saudi Arabia, exemplifies a potential flooding hazard due to its geographic location and proposed urbanization plans. This research aims to enhance flood hazard assessment in NEOM by applying the Fuzzy Analytical Hierarchy Process (FAHP) in combination with Geographic Information System (GIS). Acknowledging traditional limitations related to data availability and parameter selection consensus, the study carefully selects parameters such as drainage density, elevation, slope, rainfall, land use/land cover (LULC), soil type, normalized difference vegetation index (NDVI), and topographic wetness index (TWI). The 30 m DEM was used to derive Drainage Density, Slope, and TWI while LULC data helped assess land cover changes. Rainfall data and soil type information are integrated to evaluate their impact on flood susceptibility. NDVI is employed to analyze vegetation cover. Utilizing ArcGIS Pro’s weighted overlay model, the criteria were combined to generate the final flood susceptibility map. The research outcomes manifest in a flood susceptibility map categorizing areas into seven distinct susceptibility classes, ranging from ‘very low’ to ‘very high.’ A quantitative breakdown in a summary table provides insights into the proportional distribution of flood risk. Results indicate a significant portion of NEOM falls within varying degrees of moderate susceptibility range with relatively limited distribution of flood susceptibility on the extremes, equating to areas with ‘low to moderate’ susceptibility is 4,322.8 km2, areas with ‘moderate’ susceptibility is 5,109.69 km2, areas with ‘moderate to high’ is 4,081.39 km2. The flood susceptibility map developed in this study can shed insights on potential optimum areas for flood mitigation measures (i.e., optimum locations for establishing stormwater collection points).

Enhancing the city-level thermal environment through the strategic utilization of urban green spaces employing geospatial techniques.

Smart urban planning needs to have a multicriteria-based approach to prevent the deteriorating local thermal climate. Maximizing the cooling potential using the available grey infrastructure would be the utmost priority of future smart cities. Remote sensing and GIS can be the appropriate tools to develop a climate-resilient urban planning framework. Studies are needed to include different features of vertical and horizontal landscaping to mitigate heat stress and enhance liveability at the city level. With this goal, the current work outlined a holistic approach to efficiently using green spaces with minimal reconstruction. The problem of regional climate threat was evaluated with urban heat island characterization. Moran's I clustering identified nearly 12% of the study area to be under considerable heat stress during summer days. Multiple techniques, such as mapping local climate zones, segment mean shift-based roof extraction, vegetation index computation, solar azimuth-based green wall site selection, etc., were applied to formulate solutions and provide an integrated method for city-level environment enhancement. A considerable area was identified as most suitable for green roof cover, and it was also computed that the transition towards green roof at only these locations may bring down the maximum heat island intensity by 0.74°C. Additionally, solar zenith, illumination effect, and building height information were combined to create a distinct method where vertical plantation would flourish exceptionally. A rigorous assessment of more than 130 urban green spaces further quantified the relation between landscape geometry and cooling effect to provide optimum green space designs for future urban planning.

Impact of high-speed rail on city attractiveness

Numerous studies have delved into the socioeconomic impacts of High-Speed Rail (HSR) on urban development, examining dimensions, such as economics, environment, and tourism. However, a consistent evaluation framework to measure the overall influence of HSR on city attractiveness remains elusive. This study addresses this gap by utilizing confirmatory factor analysis (CFA) to identify pivotal factors driving city attractiveness and employing structural equation modeling (SEM) to examine the mechanism through which HSR shapes city attractiveness. The analysis confirms that, despite economic performance, urban amenities such as housing, education, and technology play significant roles in improving city attractiveness. Further analysis demonstrates that HSR has different influential mechanisms on city attractiveness across two phases: introduction and operation. The major difference lies in if HSR can directly affect economic performance. Moreover, the analysis also shows the spatiotemporal variance in the impact of HSR on city attractiveness. These findings provide important insights for urban planners, enabling the formulation of more effective strategies for future infrastructure investment and city development.

On Vehicular Data Aggregation in Federated Learning

Vehicular federated learning systems will be beneficial to predicting traffic events in future intelligent cities. However, they might leak private information upon model updates. Hence, an honest but curious server could infer private information, such as the route of a vehicle. In this study, we elaborate on the nature of such privacy leakage caused by gradient sharing. With a simulated scenario, we focus on determining who is in danger of privacy threats and how successful a route inference attack can be. Results indicate that vanilla federated learning exposes intra-city and commuter traffic to successful location inference attacks. We also found that an adversarial aggregator server successfully infers the moving time of vehicles traveling during low-traffic periods.