Smart Cities, Volume 3, Issue 4 (December 2020) – 18 articles

Wireless Underground Communication (WUC) is an emerging field that is being developed continuously. It provides secure mechanism of deploying nodes underground which shields them from any outside temperament or harsh weather conditions. This paper works towards introducing WUC and give a detail overview of WUC. It discusses system architecture of WUC along with the anatomy of the underground sensor motes deployed in WUC systems. It also compares Over-the-Air and Underground and highlights the major differences between the both type of channels. Since, UG communication is an evolving field, this paper also presents the evolution of the field along with the components and example UG wireless communication systems. Finally, the current research challenges of the system are presented for further improvement of the WUCs. Full article

This paper reports the results of a recently concluded R&D project, SCALS (Smart Cities Adaptive Lighting System), which aimed at the development of all hardware/software components of an adaptive urban smart lighting architecture allowing municipalities to manage and control public street lighting lamps. The system is capable to autonomously adjust street lamps’ brightness on the basis of the presence of vehicles (busses/trucks, cars, motorcycles and bikes) and/or pedestrians in specific areas or segments of the streets/roads of interest to reduce the energy consumption. The main contribution of this work is to design a low cost smart lighting system and, at same time, to define an IoT infrastructure where each lighting pole is an element of a network that can increase their amplitude. More generally, the proposed smart infrastructure can be viewed as the basis of a wider technological architecture aimed at offering value-added services for sustainable cities. The smart architecture combines various sub-systems (local controllers, motion sensors, video-cameras, weather sensors) and electronic devices, each of them in charge of performing specific operations: remote street segments lamp management, single street lamp brightness control, video processing for vehicles motion detection and classification, wireless and wired data exchanges, power consumptions analysis and traffic evaluation. Two pilot sites have been built up in the project where the smart architecture has been tested and validated in real scenarios. Experimental results show that energy savings of up to 80% are possible compared to a traditional street lamp system. Full article

The present study seeks to explore the concept of “smart economy” through the definition of the smart city. It also presents smart city subsystems and the smart city model. It focuses on smart and creative startups within the smart city model. The research examines medium-sized cities in the Visegrád countries (Czech Republic, Slovakia, Poland, Hungary) with a population ranging from 100,000 to 1 million inhabitants for startups. The research question is: Where are the medium-sized cities in the Visegrád countries that are both startup centers and smart cities? In the course of the research, the term “smart cities” was based on the definition set by the European Commission and the definition of startup centers was made using data analysis of the American Crunchbase database. As a result of the two studies, it can be concluded that there are no cities in the Visegrád countries with an above average level of both startup presence and smart cities. Full article

The rapidly growing use of digital technologies in urban contexts is generating a huge and increasing amount of data, providing real-time information about the urban environment and its inhabitants. The unprecedented availability of data allows us to not only improve advanced knowledge and gain a deeper understanding of urban dynamics, but also enact data evidence-based transformative processes and actions in the direction of smarter, more sustainable, resilient, and socially equitable cities. In this context, the literature on smart cities has recently expressed the need to more deeply involve urban visions and communities in the process of regeneration. This paper aims to analyze how big data can be useful in understanding the effectiveness of small pilot actions of regeneration and reactivation in valuable cultural heritage (CH) urban environments. Pilot actions were developed in the context of the European Union funded project “ROCK—Regeneration and Optimization of cultural heritage in Creative and Knowledge cities” (GA730280). The paper analyses data collected by the ROCK City People Flow tool, in different use and time conditions, in two central squares of Bologna (Italy), in order to rate event successes, spatial transformation effects, and regeneration tactics responses. Data confirm the complexity of interpreting phenomena in such contexts but also provide useful indications for future planning. Full article

Before implementing an Urban Freight Transport (UFT) solution, certainty is required about the effectiveness of the considered alternatives. Selecting an effective solution necessitates the engagement of all stakeholders involved in the management of the UFT system. The aim of the study is the formulation of a common assessment platform for facilitating the selection of the most appropriate UFT solution, taking into account the solutions’ effectiveness and the stakeholder perceptions and consensus. Solution maturity, social acceptance, and user uptake, which are considered as the main drivers of stakeholders’ engagement, are evaluated based on a real time Delphi survey, in parallel with solutions’ sustainability dimensions (economy and energy, environment, society, transport, and mobility). The Delphi method emerges as a suitable tool in this direction as stakeholders’ subjective judgments, and not analytical techniques, are required. The platform is demonstrated through the assessment of ten UFT solutions by 184 stakeholders (public authorities, supply chain operators, and other interested groups) who reside in cities across the world. The results of the demonstration showed that Intelligent Transportation Systems (ITS) for freight monitoring and electric vehicles are the highest rated solutions, while drone deliveries are the lowest, reaching respectively the highest and lowest consensus levels. Full article

The charging infrastructure for electric vehicles faces the challenges of insufficient capacity and long charging duration. These challenges decrease the electric vehicle users’ satisfaction and lower the profits of infrastructure providers. Reservation systems can mitigate these issues. We introduce a reference architecture for interoperable reservation systems. The advantages of the proposed architecture are: it (1) considers the needs of the most relevant electric mobility stakeholders, (2) satisfies the interoperability requirements of existing technological heterogeneity, and (3) provides a classification of reservation types based on a morphological methodology. We instantiate the reference architecture and verify its interoperability and fulfillment of stakeholder requirements. Further, we demonstrate a proof-of-concept by instantiating and implementing an ad-hoc reservation approach. Our validation was based on simulations of real-world case studies for various reservation deployments in the Netherlands. We conclude that, in certain high demand situations, reservations can save significant time for electric vehicle trips. The findings indicate that a reservation system does not directly increase the utilization of the charging infrastructure. Full article

In recent years, there has been a growing interest in travel applications that provide on-site personalized tourist spot recommendations. While generally helpful, most available options offer choices based solely on static information on places of interest without consideration of such dynamic factors as weather, time of day, and congestion, and with a focus on helping the tourist decide what single spot to visit next. Such limitations may prevent visitors from optimizing the use of their limited resources (i.e., time and money). Some existing studies allow users to calculate a semi-optimal tour visiting multiple spots in advance, but their on-site use is difficult due to the large computation time, no consideration of dynamic factors, etc. To deal with this situation, we formulate a tour score approach with three components: static tourist information on the next spot to visit, dynamic tourist information on the next spot to visit, and an aggregate measure of satisfaction associated with visiting the next spot and the set of subsequent spots to be visited. Determining the tour route that produces the best overall tour score is an NP-hard problem for which we propose three algorithms variations based on the greedy method. To validate the usefulness of the proposed approach, we applied the three algorithms to 20 points of interest in Higashiyama, Kyoto, Japan, and confirmed that the output solution was superior to the model route for Kyoto, with computation times of the three algorithms of $1.9\pm 0.1$, $2.0\pm 0.1$, and $27.0\pm 1.8$ s. Full article

Traditional Artificial Intelligence (AI) technologies used in developing smart cities solutions, Machine Learning (ML) and recently Deep Learning (DL), rely more on utilising best representative training datasets and features engineering and less on the available domain expertise. We argue that such an approach to solution development makes the outcome of solutions less explainable, i.e., it is often not possible to explain the results of the model. There is a growing concern among policymakers in cities with this lack of explainability of AI solutions, and this is considered a major hindrance in the wider acceptability and trust in such AI-based solutions. In this work, we survey the concept of ‘explainable deep learning’ as a subset of the ‘explainable AI’ problem and propose a new solution using Semantic Web technologies, demonstrated with a smart cities flood monitoring application in the context of a European Commission-funded project. Monitoring of gullies and drainage in crucial geographical areas susceptible to flooding issues is an important aspect of any flood monitoring solution. Typical solutions for this problem involve the use of cameras to capture images showing the affected areas in real-time with different objects such as leaves, plastic bottles etc., and building a DL-based classifier to detect such objects and classify blockages based on the presence and coverage of these objects in the images. In this work, we uniquely propose an Explainable AI solution using DL and Semantic Web technologies to build a hybrid classifier. In this hybrid classifier, the DL component detects object presence and coverage level and semantic rules designed with close consultation with experts carry out the classification. By using the expert knowledge in the flooding context, our hybrid classifier provides the flexibility on categorising the image using objects and their coverage relationships. The experimental results demonstrated with a real-world use case showed that this hybrid approach of image classification has on average 11% improvement (F-Measure) in image classification performance compared to DL-only classifier. It also has the distinct advantage of integrating experts’ knowledge on defining the decision-making rules to represent the complex circumstances and using such knowledge to explain the results. Full article

Smart cities are especially suited for improving urban inclusion by combining digital transition and social innovation. To be smart, a city has to provide every citizen with urban spaces, public services, and common goods that are effectively affordable, whatever the citizen’s gender, culture, origin, race, or impairment. Based on two design workshops, the “Vibropod” and the “Pointe-aux-Lièvres”, this paper aims at highlighting the contributions of design fiction to the improvement of the spatial capability of hearing impaired people. This research draws its originality from both its conceptual framework, built on an interdisciplinary and intersectoral composition of arts and sciences, and its operational approach, based on the use of the DeafSpace markers and the TRIZ theory (Russian acronym for Inventive Problem Solving Theory) principles. The two design fiction workshops demonstrate that considering the singularity of the human being as an actual acoustic material constitutes an innovative opportunity to improve the role of universal design in a smart city project. By reversing the classic posture, and defining disability by looking at characteristics of the environment rather than as limits of the people themselves (their bodies or their senses), this research proposes an innovative way of addressing smart city inclusivity issues. This paper shows how increasing spatial enablement and having better control of spatial skills can offer deaf people new skills to improve the use of technology in support of urban mobility, as well as give them tools for feeling safer in urban environments. Full article

This study explores the ‘people’ and ‘place’ components of the smart city concept in order to inform its third component, ‘technology’, for augmented disability inclusion. The research objective was to reveal the capability of the universal open space design (UOSD) method in classifying key spatial factors according to their type of digital applicability as a channel or subject for information and communication technologies (ICTs). Results were derived from three Hungarian design projects presented as case studies, using the research through design (RtD) method. User needs and usage patterns, open space environmental components and types according to their tolerance towards physical modification, and relevant disability-related concepts linked to UOSD were hierarchized and interrelated to digital technologies that can replace or complement the environmental components. Findings were represented in the spatial Maslow pyramid of user needs related to the relevant spatial design concepts, open spaces public services, and digital technologies. The results showed that upper (less basic) levels of the digital Maslow pyramid related to public services other than transport and concepts other than physical accessibility lack digital completion or replacement. In particular, a more detailed and consistent knowledge about spatial–digital interrelations for sensory accessibility should be incorporated into the practical and theoretical background of “smart” UOSD. In conclusion, this paper demonstrates how the combination of the concepts of UOSD and the smart city support a more complex disability-inclusive experience in an interconnected physical, sociocultural, and digital network of open spaces. Full article

The evolving concept of ‘Smart Cities’ (SC) is today gaining global momentum in scientific and policy arenas. With the rising potential for jobs and improved lifestyle, these fast-growing cities are witnessing an ever-increasing concentration of populations and economic activities. However, the core aspect of sustainability is often overshadowed in SC by the components of economic growth. In view of the rising water, energy, and food (collectively referred to as WEF) demands in cities and the interlinkages between WEF systems, this study aims to highlight the role of SC in enhancing WEF resource efficiency from a nexus perspective. To study the current trends of SC developments first, a specific case of proposed Nagpur smart city (India) is reviewed based on document analysis and preliminary discussions with local government officials. Thereafter, bibliometric analysis (based on Scopus data) is conducted to establish a comprehensive understanding of existing SC research in varying domains of interlinked WEF systems. While the proposed Nagpur smart city is observably focused on city-centric goals with a high emphasis on infrastructure development, this study underlines the need for environmental resource conservation at a transboundary level. The key opportunities for optimizing the WEF nexus in Nagpur are then highlighted in reference to the bibliometric analysis. Full article

The building sector is currently responsible of 40% of global final energy consumption, influencing the broader energy system in terms of new electricity and heat capacity additions, as well as distribution infrastructure reinforcement. Current building energy efficiency potential is largely untapped, especially at the local level where retrofit interventions are typically enforced, neglecting their potential synergies with the entire energy system. To improve the understanding of these potential interactions, this paper proposes a methodology that links dynamic building simulation and energy planning tools at the urban scale. At first, a detailed bottom-up analysis was conducted to estimate the current and post-retrofit energy demand of the building stock. The stock analysis is further linked to a broader energy system simulation model to understand the impact of building renovation on the whole urban energy system in terms of cost, greenhouse gas emission, and primary energy consumption up to 2050. The methodology is suited to analyze the relationship between building energy demand reduction potential and clean energy sources’ deployment to shift buildings away from fossil fuels, the key priority for decarbonizing buildings. The methodology was applied to the case study city of Torino, Italy, highlighting the critical role of coupling proper building retrofit intervention with district-level heat generation strategies, such as modern district heating able to exploit low-grade heat. Being able to simulate both demand and supply future alternatives, the methodology provides a robust reference for municipalities and energy suppliers aiming at promoting efficient energy policies and targeted investments. Full article

In urban contexts, the increasing density of electronic devices equipped with Global Navigation Satellite System (GNSS) receivers and complementary positioning technologies is attracting research and development efforts devoted to an improvement of the quality of life towards the smart city paradigm. Vehicular and pedestrian positioning and navigation capabilities are among the major drivers for innovation in this process. Ultra-low-cost electronics such as smartphones and Internet of Things (IoT) sensors aim at providing accurate and reliable positioning solutions through a set of promising solutions. Among these, snapshot positioning allows to remotely perform the post-processing of GNSS signals in IoT sensor networks while Wi-Fi™ ranging and cooperative positioning provide auxiliary anchors of opportunity to enhance indoor/outdoor positioning capabilities. This paper presents an innovative platform to perform a centralised testing and assessment of such positioning and navigation technologies along with a set of results obtained in the context of the European project HANSEL, by relying on current network technologies and infrastructures (i.e., Wi-Fi™ and cellular connectivity). Full article

During hazardous events, communities can use existing social media networks to share information in real time and initiate a local disaster response. This research conducted a web-based survey to explore two behaviors around the use of social media during hurricanes: seeking help and responding to help requests. Through the survey, we sampled 434 individuals across several counties affected by 2018 hurricanes Florence and Michael, which were both designated by the National Oceanic and Atmospheric Administration as billion-dollar weather disasters. The survey questions collected data about demographics, social media use habits, perceptions towards social media, hurricane damages, and actions taken during a hurricane to seek and provide help. The Theory of Planned Behavior (TPB) was used to conceptualize and frame parameters that affect intentions and behaviors regarding the use of social media during hurricanes to seek and provide help. Survey responses are analyzed using statistical regression to evaluate hypotheses about the influence of factors on seeking help and responding to help requests. Regression analyses indicate that attitude and perceived behavioral control predict intention to access social media during a hurricane, partially supporting the TPB. Intention and experiencing urgent damages predict help-seeking behaviors using social media. Posting frequency to social media under normal conditions and the number of help requests seen during the event predict help-responding behaviors. Linear regression equations governing intention and behavior were parameterized using survey results. The factors underlying social media behavior during hurricanes as identified in this research provide insight for understanding how smart information technologies, such as personal devices and social media networks, support community self-sufficiency and hazard resilience. Full article

Carbon emission is a prominent issue, and smart urban solutions have the technological capabilities to implement change. The technologies for creating smart energy systems already exist, some of which are currently under wide deployment globally. By investing in energy efficiency solutions (such as the smart meter), research shows that the end-user is able to not only save money, but also reduce their household’s carbon footprint. Therefore, in this paper, the focus is on the end-user, and adopting a quantitative analysis of the perception of 1365 homes concerning the smart gas meter installation. The focus is on linking end-user attributes (age, education, social class and employment status) with their opinion on reducing energy, saving money, changing home behaviour and lowering carbon emissions. The results show that there is a statistical significance between certain attributes of end-users and their consideration of smart meters for making beneficial changes. In particular, the investigation demonstrates that the employment status, age and social class of the homeowner have statistical significance on the end-users’ variance; particularly when interested in reducing their bill and changing their behaviour around the home. Full article

The smart cities policy approach has been intensively implemented in European cities under the Horizon 2020 programme. However, these implementations not only reduce the interdependencies among stakeholders to technocratic Public-Private-Partnership (PPP) models, but also fail to question the identities of strategic stakeholders and how they prioritise their business/social models. These aspects are putting democracy at stake in smart cities. Therefore, this article aims to unfold and operationalise multistakeholders’ policy frameworks from the social innovation perspective by suggesting the ex-novo penta-helix framework—including public, private, academia, civic society, and social entrepreneurs/activists—to extend the triple and quadruple-helix frameworks. Based on fieldwork action research conducted from February 2017 to December 2018—triangulating desk research, 75 interviews, and three validation workshops—this article applies the penta-helix framework to map out five strategic dimensions related to (i) multistakeholder helix framework and (ii) the resulting business/social models comparatively in three follower cities of the H2020-Replicate project: Essen (Germany), Lausanne (Switzerland), and Nilüfer (Turkey). For each case study, the findings reveal: (i) a unique multistakeholder composition, (ii) diverse preferences on business/social models, (iii) a regular presence of the fifth helix as intermediaries, and (iv) the willingness to experiment with democratic arrangements beyond the hegemonic PPP. Full article

Smart city strategies developed by cities around the world provide a useful resource for insights into the future of smart development. This study examines such strategies to identify plans for the explicit deployment of artificial intelligence (AI) and robotics. A total of 12 case studies emerged from an online keyword search representing cities of various sizes globally. The search was based on the keywords of “artificial intelligence” (or “AI”), and “robot,” representing robotics and associated terminology. Based on the findings, it is evident that the more concentrated deployment of AI and robotics in smart city development is currently in the Global North, although countries in the Global South are also increasingly represented. Multiple cities in Australia and Canada actively seek to develop AI and robotics, and Moscow has one of the most in-depth elaborations for this deployment. The ramifications of these plans are discussed as part of cyber–physical systems alongside consideration given to the social and ethical implications. Full article

Today’s cities are estimated to generate 80% of global GDP, covering only about 3% of the land, but contributing to about 72% of all global greenhouse gas emissions. Cities face significant challenges, such as population growth, pollution, congestion, lack of physical and social infrastructures, while trying to simultaneously meet sustainable energy and environmental requirements. The Smart City concept intends to address these challenges by identifying new and intelligent ways to manage the complexity of urban living and implement solutions for multidisciplinary problems in cities. With the increasing number of Smart City projects being implemented around the world, it is important to evaluate their strengths and weaknesses for their future improvement and evolution track record. It is, therefore, crucial to characterize and improve the proper tools to adequately evaluate these implementations. Following the Smart City implementation growth, several Smart City Assessment tools with different indicator sets have been developed. This work presents a literature review on Smart City Assessment tools, discussing their main gaps in order to improve future methodologies and tools. Smart City Assessment can deliver important performance indicators monitoring for the evaluation of multiple benefits for different actors and stakeholders, such as city authorities, investors and funding agencies, researchers, and citizens. Full article