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The IoT and big data technologies have become essential to the functioning of both smart cities and sustainable cities, and thus, urban operational functioning and planning are becoming highly responsive to a form of data-driven urbanism. This offers the prospect of building models of smart sustainable cities functioning in real time from routinely sensed data. This in turn allows to monitor, understand, analyze, and plan such cities to improve their energy efficiency and environmental health in real time thanks to new urban intelligence functions as an advanced form of decision support. However, prior studies tend to deal largely with data-driven technologies and solutions in the realm of smart cities, mostly in relation to economic and social aspects, leaving important questions involving the underlying substantive and synergistic effects on environmental sustainability barely explored to date. These issues also apply to sustainable cities, especially eco-cities. Therefore, this paper investigates the potential and role of data-driven smart solutions in improving and advancing environmental sustainability in the context of smart cities as well as sustainable cities, under what can be labeled “environmentally data-driven smart sustainable cities.” To illuminate this emerging urban phenomenon, a descriptive/illustrative case study is adopted as a qualitative research methodology§ to examine and compare Stockholm and Barcelona as the ecologically and technologically leading cities in Europe respectively. The results show that smart grids, smart meters, smart buildings, smart environmental monitoring, and smart urban metabolism are the main data-driven smart solutions applied for improving and advancing environmental sustainability in both eco-cities and smart cities. There is a clear synergy between such solutions in terms of their interaction or cooperation to produce combined effects greater than the sum of their separate effects—with respect to the environment. This involves energy efficiency improvement, environmental pollution reduction, renewable energy adoption, and real-time feedback on energy flows, with high temporal and spatial resolutions. Stockholm takes the lead over Barcelona as regards the best practices for environmental sustainability given its long history of environmental work, strong environmental policy, progressive environmental performance, high environmental standards, and ambitious goals. It also has, like Barcelona, a high level of the implementation of applied data-driven technology solutions in the areas of energy and environment. However, the two cities differ in the nature of such implementation. We conclude that city governments do not have a unified agenda as a form of strategic planning, and data-driven decisions are unique to each city, so are environmental challenges. Big data are the answer, but each city sets its own questions based on what characterize it in terms of visions, policies, strategies, pathways, and priorities.

Software Defined Networking Technology (SDN) provides a prospect to effectively detect and monitor network security problems ascribing to the emergence of the programmable features. Recently, Machine Learning (ML) approaches have been implemented in the SDN-based Network Intrusion Detection Systems (NIDS) to protect computer networks and to overcome network security issues. A stream of advanced machine learning approaches – the deep learning technology (DL) commences to emerge in the SDN context. In this survey, we reviewed various recent works on machine learning (ML) methods that leverage SDN to implement NIDS. More specifically, we evaluated the techniques of deep learning in developing SDN-based NIDS. In the meantime, in this survey, we covered tools that can be used to develop NIDS models in SDN environment. This survey is concluded with a discussion of ongoing challenges in implementing NIDS using ML/DL and future works.

More and more cities are evolving towards the smart city concept, which brings about a tangible effect of raised life quality levels. This is confirmed by the satisfaction of inhabitants with the introduced smart solutions. It is their opinion on this issue that is crucial, as they are the main beneficiaries of these measures. This article presents a case study of a medium-sized city, which illustrates the smart city issue from an inhabitants’ perspective. An analysis of objective indices classifies a city as smart, and it is included in European lists of smart cities. It is interesting, however, to see how the inhabitants themselves assess the city in the context of the smart solutions in place. Are they relevant to them? Has the quality of life increased? Are they satisfied with the individual aspects of city functioning? What solutions are they awaiting? What areas require changes? The involvement of inhabitants and the public participation level were also assessed. The questionnaire survey results indicated whether the city can be classified as a smart city of the future and identified the spheres of the city’s activities that need improvement. The main conclusions are that inhabitants have a positive perception of a city’s smart services provided that their implementation results in an enhanced quality of life. At the same time, even though inhabitants are aware of the smart services introduced, they do not fully use them, which may be due to their low attractiveness, a lack of promotion on the part of the city, or a lack of equipment readiness.

This paper is dedicated, both theoretically and conceptually, to a methodical approach towards the efficiency evaluation of proposed smart city solutions. The implementation of smart solutions in proposed projects and activities is supported by a complex assessment of benefits and costs as part of a cost benefit analysis (CBA) with the goal of maximizing the efficiency of such a solution, especially in the case of public activities for which it is typical to lack a market evaluation. A smart solution can be defined as an innovative and functional approach towards solving situations in a responsible way and with positive consequences for society. These smart solutions represent the core of the smart city concept, which together with the smart region concept presents a new economic domain where new markets or market segments offering innovative and intelligent (tangible and intangible) solutions for said cities and regions can be developed. CBA and feasibility analyses represent suitable tools for evaluation of socially and economically acceptable projects and their implementation in real life. The efficiency of these solutions is then proved by benefit and cost comparisons under the condition that these outcomes are acceptable for all stakeholders. Methodically, the paper is structured inductively. The detailed literature review provides the basis for a formulation of general principles of using a CBA for innovative smart city solution efficiency evaluations based on chosen cases, for example, from the Moravia Silesian region. Due to the originality of each submitted project, it is possible to use this proposed methodical approach of CBA applications as a primary analytical frame and it is necessary to add the specific attributes of each solution that is being evaluated.

The monitoring of forest biomass stock volumes in larger operations is typically conducted irregularly, either by tracking cargo arrivals or by using simple manual measurement methods. The objective of this study was to assess the accuracy of smart methods based on laser scanning technology, integrated into mobile phones and a handheld laser scanner, for measuring smaller piles of forest chips. For the experiment, a total of 50 m³ of fiberwood logs were chipped and distributed into four piles. The smart solutions selected for laser scanning of forest biomass in this study were the Stonex Geoslam X120 GO handheld laser scanner and the iPhone 14 Pro Max equipped with a LiDAR sensor. The results were influenced by the selected conversion coefficient and the exclusion of small scattered fragments of forest chips around the piles, which were not included in the final volume calculation. The smallest discrepancy identified by the smart solutions was 3 m³ (6%) of woody mass. The findings demonstrated that the smart solutions utilizing LiDAR technology offer good affordability, ease of use, and satisfactory accuracy. They are user-friendly and provide quick results.

Ecological urbanism is seen today as one of the keys towards unlocking the quest for a low-carbon or fossil fuel–free society. Global and local policies promote and advocate the eco–city as the most environmentally sound model of sustainable urbanism. It is argued that the eco–city strategies and solutions are expected to deliver positive outcomes in terms of minimal demand on energy resources and thus minimal environmental impacts. Moreover, it has recently been suggested that the eco-city needs to embrace and leverage what advanced ICT has to offer, particularly with regard to sustainable energy systems, so as to improve and advance its contribution to the goals of environmental sustainability. This paper examines how the eco–city especially its core environmental dimension is practiced and justified in urban planning and development with respect to sustainable energy systems and their integration with data-driven smart technologies at the district level. To illuminate this urban phenomenon accordingly, a descriptive case study is adopted as a qualitative research methodology where the empirical basis is formed by urban planning and development documents combined with secondary data and scientific literature. To provide a theoretical foundation and produce a rationale for this study, this paper first provides a state–of–the–art review of the field of ecological urbanism in terms of its foundations, models, strategies, research issues, as well as data–driven smart technological trends. This study shows that the Eco-city District of Stockholm Royal Seaport uses green energy and data-driven smart technologies as the key strategies and solutions for achieving the environmental objectives of sustainable development in terms of lowering energy consumption and mitigating pollution. This entails conserving and decreasing the demand for energy through renewable resources (i.e., sun, wind, and water), bio–fuelled Combined Heat Power system, large-scale smart grid system, energy management, sustainable waste management, and passive solar houses. This research enhances the scholarly community’s current understanding of the emerging phenomenon of the smart eco-city with respect to the synergic potential of the integration of its sustainable energy strategies with data-driven technology solutions for advancing environmental sustainability.

ContextHere we develop a practical framework (Mosaico) and report a real-world example of early implementation of a Fire-Smart Territory (FST) in Sierra de Gata-Las Hurdes region of central Spain.ObjectivesWe aimed to assess the impact of landscape changes induced by Local Land Managers (LLM; indirect prevention) on simulated fire spread under different governance scenarios developed in 2016–2021.MethodsFollowing a participatory process in the region, we received 250 proposals for intervention (49.6% from agriculturalists, 22.8% from forest producers-mainly resin tappers-, and 27.6% from shepherds). From the 94 (37.6%) proposals implemented by the end of the study, we quantified changes in fuel models over the whole territory (Scenario 1, S1). Then, we simulated fires in 20 ignition points to estimate area burned in S1 and three other governance scenarios.ResultsTo date, the sole intervention of LLMs results in a low to moderate impact (current mean 10.5; median 1.8), which can be explained by the high frequency of small-scale interventions (agriculture) and the comparatively modest impact on fuel reduction of large-scale interventions (livestock grazing). A combination of LLM and public actions is needed to reach a more substantial reduction of burned area (S2-S3, mean % impact 14.1–18.9; median 6.9–10.8). Relaxing legal/administrative constraints to allow large private intervention would result in the greatest attainable impact on burned area (S4, mean 25.0; median 17.8). Adaptive management of Mosaico approach must be focussed on improving LLM capacity to modify larger portions of the territory and prioritizing critical areas such as fire propagation nodes.

The wastewater sector paradigm is shifting from wastewater treatment to resource recovery. In addition, concerns regarding sustainability during the operation have increased. In this sense, there is a need to break barriers (i.e., social, economic, technological, legal, etc.) for moving forward towards water resource recovery facilities and demonstration case studies can be very effective and insightful. This paper presents a new water resource recovery case study which is part of the Horizon 2020 EU Project “Achieving wider uptake of water-smart solutions—Wider Uptake”. The final aim is to demonstrate the importance of a resource recovery system based on the circular economy concept. The recovery facilities at Palermo University (Italy) are first presented. Afterwards, the resource recovery pilot plants are described. Preliminary results have underlined the great potential of the wastewater treatment plant in terms of resources recovery and the central role of the University in fostering the transition towards circular economy. The fermentation batch test highlighted a volatile fatty acids (VFAs) accumulation suitable for polyhydroxyalkanoates (PHAs) production. The results of static adsorption and desorption tests showed that the highest amount of adsorbed NH4+ was recorded for untreated and HCl-Na treated clinoptilolite.

In this work, the impact of the Coronavirus disease 2019 (COVID-19) virus in Italy is presented. This pandemic disease determined a crisis and national emergency in all parts of the world. A short vision of measures taken by the Italian Government with a view on information and communication technologies (ICT) that could allow a better management of the pandemic and a faster recovery from the national crisis is provided. The Italian lockdown has strict implications for the society from an economical, mental-health and social points of view. Novel information and communication technologies (ICT) could mitigate the impact of COVID-19 outbreak allowing novel ways to learn, to teach, to work and to live. Some insights on Internet of Things, smart tracing and tracking solutions are summarised. Moreover, some statistics on the network traffic and learning platforms used in this lockdown period are presented.

Smart campus, as a high-end form of a smart education system and a mini-scopic version of a smart city, has received increasing research and attention globally. The existing smart campus concepts are mostly technology-driven, which simply introduces interconnection from a technological perspective to serve its residents but not necessarily adhering to the needs and interests of stakeholders in such a community. To fill this gap, this study presents a human-centred approach for smart campus design and development, where a user case survey study is undertaken in Hong Kong primary and secondary schools. The overall aim of the survey is to accurately and timely capture and understand the perspectives of school stakeholders on education applications in the context of the smart campus. The findings from survey analysis are presented, with insights and suggestions for future smart campus development provided. The findings in this study are also expected to result in a benchmark reference of the smart campus concept for international educational providers, government, and technology companies that will deliver smart solutions.