Search Results (31)

Intelligent transport systems are revolutionising all aspects of modern life, increasing the efficiency of commerce, modern living, and international travel. Intelligent transport systems are systems of systems comprised of cyber, physical, and social nodes. They represent unique opportunities but also have potential threats to system operation and correctness. The emergent behaviour in Complex Cyber–Physical–Social Systems (C-CPSSs), caused by events such as cyber-attacks and network outages, have the potential to have devastating effects to critical services across society. It is therefore imperative that the risk of cascading failure is minimised through the fortifying of these systems of systems to achieve resilient mission assurance. This work designs and implements a programmatic model to validate the value of cascading failure simulation and analysis, which is then tested against a C-CPSS intelligent transport system scenario. Results from the model and its implementations highlight the value in identifying both critical nodes and percolation of consequences during a cyber failure, in addition to the importance of including social nodes in models for accurate simulation results. Understanding the relationships between cyber, physical, and social nodes is key to understanding systems’ failures that occur because of or that involve cyber systems, in order to achieve cyber and system resilience. Full article

Urban decarbonisation requires governance models that overcome the fragmentation and rigidity of traditional urban planning. This article presents a systemic and digital framework for managing urban decarbonisation portfolios aligned with the EU Mission for Climate-Neutral and Smart Cities. Grounded in systems thinking and portfolio theory, this study develops an analytical taxonomy and an interactive digital tool to support strategic coordination, multistakeholder collaboration, and adaptive decision-making. The framework is empirically validated through the case of Madrid’s Climate City Contract, demonstrating its functionality and transferability. Using a mixed-method approach—combining co-creation workshops, interviews, document analysis, and iterative prototyping—this research maps interdependencies among projects, actors, and levers of change. The digital tool enables real-time visualisation of collaboration patterns, gaps, and synergies, enhancing strategic foresight and coordination capacity. Findings reveal that 75% of initiatives in Madrid’s CCC address climate adaptation, 80.36% are linked to knowledge generation, and key anchor projects serve as integrative hubs within the portfolio. This study concludes that the portfolio approach strengthens systemic innovation and reflexive governance by integrating digital infrastructures with collaborative planning processes. While challenges persist—including data integration, institutional capacity, and political dynamics—this research offers a replicable methodology for embedding mission-oriented strategies into urban governance. The digital portfolio emerges as a complementary governance tool that enhances transparency, organisational learning, and alignment across governance levels. Full article

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring an interdisciplinary approach and an innovative planning strategy. This study aims to explore potential ways of achieving synergies between NBSs and RESs to contribute to urban resilience and climate neutrality. Focusing on the railway station district in western Thessaloniki (Greece), this research is situated within the ReGenWest project, part of the EU Cities Mission. This study develops a comprehensive, well-structured framework for integrating NBSs and RESs, drawing on principles of urban planning and energy systems to address the area’s specific spatial and ecological characteristics. Using the diverse typologies of open spaces in the district as a foundation, this research analyzes the potential for combining NBSs with RESs, such as green roofs with photovoltaic panels, solar-powered lighting, and solar parking shaders, while assessing the resulting impacts on ecosystem services. The findings reveal consistent benefits for cultural and regulatory services across all interventions, with provisioning and supporting services varying according to the specific solution applied. In addition, this study identifies larger-scale opportunities for integration, including the incorporation of NBSs and RESs into green and blue corridors and metropolitan mobility infrastructures and the development of virtual power plants to enable smart, decentralized energy management. A critical component of the proposed strategy is the implementation of an environmental monitoring system that combines hardware installation, real-time data collection and visualization, and citizen participation. Aligning NBS–RES integration with Positive Energy Districts is another aspect that is stressed in this paper, as achieving carbon neutrality demands broader systemic transformations. This approach supports iterative, adaptive planning processes that enhance the efficiency and responsiveness of NBS–RES integration in urban regeneration efforts. Full article

The growing use of unmanned aerial vehicles (UAVs) in diverse fields such as disaster recovery, rural regions, and smart cities necessitates effective dynamic drone network establishment techniques. Conventional optimization techniques like genetic algorithms (GAs) and particle swarm optimization (PSO) are weak when it comes to real-time adjustment to the environment and multi-objective constraints. This paper proposes a hybrid optimization framework combining genetic algorithms and reinforcement learning (RL) to improve the deployment of drone networks. We integrate Q-learning into the GA mutation process to allow drones to adaptively adjust locations in real time under coverage, connectivity, and energy constraints. In the scenario of large-scale simulations for wildfire tracking, disaster response, and urban monitoring tasks, the hybrid approach performs better than GA and PSO. The greatest enhancements are 6.7% greater coverage, 7.5% less average link distance, and faster convergence to optimal deployment. The proposed framework allows drones to establish strong and stable networks that are dynamic in nature and adapt to dynamic mission demands with efficient real-time coordination. This research has important applications in autonomous UAV systems for mission-critical applications where adaptability and robustness are essential. Full article

Multirotor drones play an increasingly significant role in smart cities and are among the most widely discussed emerging technologies. They are expected to support various applications such as package delivery, data collection, traffic policing, surveillance, and medicine. As part of their services, future drones should be able to solve the last-mile challenge and land safely in urban areas. This paper addresses the path planning task for an autonomous drone searching for a landing place in an urban environment. Our algorithm uses a novel multi-resolution probabilistic approach in which visual information is collected by the drone at decreasing altitudes. As part of the exploration task, we present the Global Path Planning (GPP) problem, which uses probabilistic information and the camera’s field of view to plan safe trajectories that will maximize the search success by covering areas with high potential for proper landing while avoiding no-fly zones and complying with time constraints. The GPP problem is formulated as a minimization problem and then is shown to be NP-hard. As a baseline, we develop an approximation algorithm based on an exhaustive search, and then we devise a more complex yet efficient heuristic algorithm to solve the problem. Finally, we evaluate the algorithms’ performance using simulation experiments. Simulation results obtained from various scenarios show that the proposed heuristic algorithm significantly reduces computation time while keeping coverage performance close to the baseline. To the best of our knowledge, this is the first work referring to a multi-resolution approach to such search missions; further, in particular, the GPP problem has not been addressed previously. Full article

This study provides a detailed analysis of land use and land cover (LULC) changes at the district level within the Delhi–Mumbai Industrial Corridor (DMIC) from 2001 to 2021. Using the Indian Meteorological Department’s sub-divisional framework and MODIS data across seven primary LULC classes, the analysis is instrumental in informing infrastructure planning for existing and future smart cities and industrial clusters within the DMIC. The key findings reveal a yearly increase of 3031.40 sq. km. per year in agricultural land, with decreases in shrubland, grassland, and bareland of −1774.72 sq. km. per year, −1119.62 sq. km. per year, and −203.76 sq. km. per year, respectively. On the other hand, forests grew by a modest 148.14 sq. km. per year, while waterbodies and built-up lands saw minor increases of 55.73 sq. km. and 21.48 sq. km. per year. Ecologically Sensitive Areas (ESAs) were evaluated for LULC changes. The smart cities of Pune and Thane serve as excellent examples of balanced urban development and natural growth management. However, the study also highlights the need for further research to investigate LULC impacts on climatic variables, advocating for a regional planning approach in the DMIC. Full article

With the increasing demand for high data rates, low delay, and extended battery life, managing massive machine-type communication (mMTC) in the beyond 5G (B5G) context is challenging. MMTC devices, which play a role in developing the Internet of Things (IoT) and smart cities, need to transmit short amounts of data periodically within a specific time frame. Although blockchain technology is utilized for secure data storage and transfer while digital twin technology provides real-time monitoring and management of the devices, issues such as constrained time delays and network congestion persist. Without a proper data transmission strategy, most devices would fail to transmit in time, thus defying their relevance and purpose. This work investigates the problem of massive random access channel (RACH) attempts while emphasizing the energy efficiency and access latency for mMTC devices with critical missions in B5G networks. Using machine learning techniques, we propose an attention-based reinforcement learning model that orchestrates the device grouping strategy to optimize device placement. Thus, the model guarantees a higher probability of success for the devices during data transmission access, eventually leading to more efficient energy consumption. Through thorough quantitative simulations, we demonstrate that the proposed learning-based approach significantly outperforms the other baseline grouping methods. Full article

Three-dimensional reconstruction is a key technology employed to represent virtual reality in the real world, which is valuable in computer vision. Large-scale 3D models have broad application prospects in the fields of smart cities, navigation, virtual tourism, disaster warning, and search-and-rescue missions. Unfortunately, most image-based studies currently prioritize the speed and accuracy of 3D reconstruction in indoor scenes. While there are some studies that address large-scale scenes, there has been a lack of systematic comprehensive efforts to bring together the advancements made in the field of 3D reconstruction in large-scale scenes. Hence, this paper presents a comprehensive overview of a 3D reconstruction technique that utilizes multi-view imagery from large-scale scenes. In this article, a comprehensive summary and analysis of vision-based 3D reconstruction technology for large-scale scenes are presented. The 3D reconstruction algorithms are extensively categorized into traditional and learning-based methods. Furthermore, these methods can be categorized based on whether the sensor actively illuminates objects with light sources, resulting in two categories: active and passive methods. Two active methods, namely, structured light and laser scanning, are briefly introduced. The focus then shifts to structure from motion (SfM), stereo matching, and multi-view stereo (MVS), encompassing both traditional and learning-based approaches. Additionally, a novel approach of neural-radiance-field-based 3D reconstruction is introduced. The workflow and improvements in large-scale scenes are elaborated upon. Subsequently, some well-known datasets and evaluation metrics for various 3D reconstruction tasks are introduced. Lastly, a summary of the challenges encountered in the application of 3D reconstruction technology in large-scale outdoor scenes is provided, along with predictions for future trends in development. Full article

COVID has expedited and expanded the already precarious smart city development in India with the multitude of ‘smart’ COVID responses—broadly known as CovTech—introduced since the early days of the global pandemic. This paper offers an analysis of the scope and scale of smart responses to COVID in the first 20 cities prioritized for smart city implementation—as part of the Smart Cities Mission in India. The analysis unravels the diversity within the smart COVID response, as 125 COVID applications, 14 COVID-War-Rooms, and numerous examples of smart public place initiatives are discussed. The findings include a typology of COVID applications and shed light on the operations of COVID-War-Rooms throughout the nation. The learnings point toward a mostly top-down approach to smart COVID response. Yet, early evidence indicates the existence of an alternative subaltern smart COVID response to provide bottom-up support to the most vulnerable groups, filling the gaps in the top-down approach. More research is required to thoroughly understand the scope and scale of the subaltern smart response to COVID. Full article

Fully autonomous trajectory planning for multiple unmanned aerial vehicles (UAVs) is significant for building the next generation of the logistics industry without human control. This paper presents a method to enable multiple UAVs to fly in the same trajectory without collision. It benefits several applications, such as smart cities and transfer goods, during the COVID-19 pandemic. Different types of nonlinear state estimation are deployed to test the position estimation of drones by treating the information from AirSim as offline dynamic data. The obtained global positioning system sensor data and magnetometer sensor data are determined as the measurement model. The experiment in the simulation is separated into (1) the localization state, (2) the rendezvous state, in which the proposed rendezvous strategy is presented by using the relation between velocity and displacement through the setting area, and (3) the full mission state, which combines both the localization and rendezvous states. The localization state results show the best RMSE in the case of full GPS available at 0.21477 m and 0.25842 m in the case of a GPS outage during a period of time by implementing the ensemble Kalman filter. Similarly, the ensemble Kalman filter performs well with an RMSE of 0.5112414 m in the rendezvous state and demonstrates exceptional performance in the full mission state. Moreover, the experiment is implemented in a real-world situation with some basic drone kits as proof that the proposed rendezvous strategy can truly operate. Full article

The sustainability of a smart city development depends on the interpretations and prioritization driven by the key actors. Currently; the “top-down” smart city implementation in many countries is at risk of disengaging with local stakeholders and further widening the social disparities in the cities. This paper presents the socio-political contexts of a smart city, the citizens’ perspectives and awareness using Phuket, and Thailand as a case study. Desktop research was used to describe the context of the smart city policy; key driving organizations; budget allocation; and the guiding vision and mission statements at the local level. A survey of 409 residents was conducted to assess their awareness and willingness to participate in Phuket Smart City (PSC) activities as well as internet behavior and communication channels. The findings reveal uneven awareness of PSC across demographic groups. PSC was more familiar to the middle-aged; highly educated; high-income; and locals with leadership positions and living near the city center. A perceived lack of knowledge, time, information, and relevance affected the residents’ willingness to be involved in smart city development. Active communication and grass-root engagement are needed to improve public awareness and engagement in smart city implementation and achieve meaningful and equitable development. Full article

This paper presents an exploratory activity with a drone inspection service for environmental control. The aim of the service is to provide technical support to decision-makers in environmental risk management. The proposed service uses IoT for the interaction between a mobile application, a Smart City platform, and an Unmanned Aircraft System (UAS). The mobile application allows the users to report risky situations, such as fire ignition, spills of pollutants in water, or illegal dumping; the user has only to specify the class of the event, while the geographical coordinates are automatically taken from device-integrated GPS. The message sent from the mobile application arrives to a Smart City platform, which shows all the received alerts on a 3D satellite map, to support decision-makers in choosing where a drone inspection is required. From the Smart City platform, the message is sent to the drone service operator; a CSV file defining the itinerary of the drone is automatically built and shown through the platform; the drone starts the mission providing a video, which is used by the decision-makers to understand whether the situation calls for immediate action. An experimental activity in an open field was carried out to validate the whole chain, from the alert to the drone mission, enriched by a Smart City platform to enable a decision-maker to better manage the situation. Full article

In the context of automation and digitalization technologies and due to the existing trends of re-urbanization, autonomous vehicles for execution of services such as package delivery, transportation, vegetation care and street cleaning are considered innovative solutions. This paper presents a concept and implementation of a system developed to plan and deliver packages within pedestrian areas, using autonomous vehicles. The novelty of the system lies in the systematic view of this use case, which considers all stakeholder views from the CEP (courier, express, and parcel services) provider, traffic participants, and customers and where the technical and technological innovation is guided by interactivity with the users. This work outlines the design and integration of user interaction, the developed vehicles within the fleet designed for operating within pedestrian environments, and localization and navigation strategies. After the vehicles were approved and certified from a technical point of view to operate in pedestrian areas, the entire system was tested and evaluated in a new city district of Heilbronn with approximately 800 inhabitants. In the last six weeks of experiments, 572 packages were delivered in an autonomous way. The interactive way of planning and executing services on demand led, according to a market study in Heilbronn, to an increased acceptance of the users for autonomous package delivery services from 76% to 91%. Full article

This paper investigates on long-term challenges faced by local governments. Using empirical evidence from Estonia, this paper aims to help fill a research gap in that there is a lack of a systematic approach on how to analyze common urban challenges via direct involvement of local governments. In terms of conceptual framework, a unique combination of public value theory and mission-oriented innovation is proposed. The data is collected via questionnaire, interviews and workshops involving up to 35 local governments. It is important that instead of current problems relating only to one city, this study focuses on finding shared, long-term challenges and, from them, generates a list of top 10 challenges. This provides valuable input to initiating new research and innovation projects in the key, smart city domains (e.g., energy, mobility, built environment, governance and data). Full article

The Sustainable Development Goals (SDGs) aim at providing a healthier planet for present and future generations. At the most recent SDG summit held in 2019, Member States recognized that the achievements accomplished to date have been insufficient to achieve this mission. This paper presents a comprehensive literature review of 227 documents contextualizing outdoor lighting with SDGs, showing its potential to resolve some existing issues related to the SDG targets. From a list of 17 goals, six SDGs were identified to have relevant synergies with outdoor lighting in smart cities, including SDG 3 (Good health and well-being), SDG 11 (Sustainable cities and communities), SDG 14 (Life below water) and SDG 15 (Life on land). This review also links efficient lighting roles partially with SDG 7 (Affordable and clean energy) and SDG 13 (Climate action) through Target 7.3 and Target 13.2, respectively. This paper identifies outdoor lighting as a vector directly impacting 16 of the 50 targets in the six SDGs involved. Each section in this review discusses the main aspects of outdoor lighting by a human-centric, energy efficiency and environmental impacts. Each aspect addresses the most recent studies contributing to lighting solutions in the literature, helping us to understand the positive and negative impacts of artificial lighting on living beings. In addition, the work summarizes the proposed solutions and results tackling specific topics impacting SDG demands. Full article