Future Smart Cities Research Articles

IEEE Access Special Section Editorial: Future Generation Smart Cities Research—Part II: Services, Applications, Case Studies, and Policymaking Considerations For Well-Being

The future generation of smart cities is a very timely and attractive topic for the research community worldwide. The evolution of this generation is oriented toward providing innovative services and policymaking to guarantee the well-being of citizens. Research on smart cities is maturing and the question of securing the well-being of cities’ inhabitants is increasingly attracting the attention of researchers, practitioners, and policymakers. Considering the challenges and opportunities cities/urban spaces generate, today the imperative is to examine how targeted research and cutting-edge innovation can be effectively communicated to all stakeholders. Thus, synergies emerging at the researchinnovation- policymaking nexus can be exploited and city dwellers’ well-being can be enhanced. Pervasive computing, big data analytics, crowdsourcing, and other timely technologies, including user behavior, brand popularity, recommender systems, and social media analytics, bear the promise and potential that viable solutions to key problems and challenges specific to the future generation of smart cities will be found. The objective of this Special Section in IEEE ACCESS is to examine this promise and potential from a variety of complementary interdisciplinary perspectives, including computing/ ICT, political economy, public policy, innovation, and entrepreneurship.

Analysis based traffic flow control decision using IoT sensors

The traffic flow control decision plays a crucial role in many of the main aspects of a future smart city. It is highly configurable and costly for a higher standard of service. This paper proposes an analysis-based traffic flow control decision model (ATFCD) for smarter, better, and efficient regulation of transport services. In this paper, the proposed model explores the extensive use of a well-known paradigm, the Internet of Things (IoT). In this model, the sensors will be used to identify and count cars, riders, on-road pedestrians, trams, subways, and ferries. The proposed model will be applicable in real-time monitoring of the traffic flow, and the data collected from the sensors will be processed further and decision making will be done based on the collected data analysis. The proposed model is focusing to reduce the traffic congestion on highways and busy roads.

Node Value and Content Popularity‐Based Caching Strategy for Massive VANETs

The high‐speed dynamic environment and massive information transmitted via wireless communications in the vehicular ad hoc networks (VANETs) pose a great challenge to privacy and security. To overcome this issue, use of the content‐centric networking (CCN) provides a potential and practical solution. In‐network caching is a main feature for future smart cities, in which the content is mainly placed in network nodes. Therefore, how to effectively select the cache locality and cache content is essential to improve the overall network performance, which is an inevitable trend. With these observations, this article proposes a caching strategy based on the node value and content popularity (NVCP) for the massive VANET scenario. In the proposed NVCP scheme, different from the traditional caching strategies, we evaluate the node value from three aspects: the connectivity, intermediary, and eigenvector centralities, synthetically, since the content with different types of popularity is placed in nodes with different values, resulting in the redundancy deterioration and diversity improvement for the content. The proposed caching strategy is evaluated by the stochastic network topology with multifactors, which provides different impacts on the system performance. Simulation results show that the NVCP outperforms the traditional cache strategies for 6G‐CCN in terms of the cache hit ratio, average hop count, and transmission latency. Moreover, placing the content in the neighbor nodes is also introduced to further improve the utilization of the cache space and achieve better cache performance.

Natural language processing-based characterization of top-down communication in smart cities for enhancing citizen alignment

Many city governments have implemented promising smart initiatives to make cities more efficient, livable, and ecological. To harness the full potential of smart city initiatives, it is vital for policymakers to align citizens with the project objectives. This study comprehensively characterizes and classifies top-down announcements formulated by city developers into six alignment categories (i.e., smart economy, smart people, smart governance, smart mobility, smart environment, and smart living) using natural language processing. The proposed framework consists of five main processes: (1) web scraping-based extraction of announcements of four smart cities – Boston, Helsinki, Seoul, and Taipei, (2) text data preprocessing, (3) latent Dirichlet allocation-based modeling of strategic topics, (4) quantification of inter-topic similarities using Hellinger distance, and (5) comparison of top-down communication trends with real-world levels of urban performance. Through the comparative analysis of top-down communication trends and actual urban performances, the top-down discourses of smart cities were deconstructed as a reflection of wider political programs developed to enhance citizen alignment and urban performances. Furthermore, inter-topic similarities were also quantified to reflect whether communication strategies are multidisciplinary and city-tailored. In conclusion, the findings of this study can enhance our understanding and provide workable guidance for future smart city development.

Multiple hydrogen-based hybrid storage systems operation for microgrids: A combined TOPSIS and model predictive control methodology

Hydrogen-based hybrid storage system has a high energy density, which can operate as the long-term storage system, and play an important role in future smart cities. In the hydrogen storage system, fuel cell, hydrogen tanks, and electrolyzer are often combined together and operating with complex electrochemical reactions. How to efficiently operate the hydrogen storage system and considering the convoluted electrochemical reactions is a problem. In addition, multiple hydrogen storage systems are often grouped together to supply the demands. Thus, cooperating the dispatching of these storage systems is another complicated problem. In this paper, we first present a two-dimension model considering temperature influences for hydrogen-based microgrid, where a regression method is adopted. Moreover, a combined allocating-and-dispatching methodology involving two layers is proposed to cooperate the multiple storage systems. Specifically, both TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and fuzzy logic are adopted as the first-layer allocating algorithm. Then, the model predictive control (MPC) is utilized as the second-layer dispatching algorithm. Based on the combined method, power is firstly allocated to hybrid storage system considering each hybrid storage system health conditions, and secondly scheduled to battery storage and hydrogen storage based on MPC method. The simulation results showed that with the combined Dematel-TOPSIS and MPC algorithm, the degradation index and operation cost were the smallest among three algorithms, and can further extend the lifetime of hybrid hydrogen storage systems in microgrids.

Future (post-COVID) digital, smart and sustainable cities in the wake of 6G: Digital twins, immersive realities and new urban economies

With the advance of 5G technologies by both academia and industry, 5G adoption is gaining widespread acceptance in numerous cities, prompting further innovations in Smart City technologies riding on the wave of the Internet of Things (IoT). However, even in its infancy stage, the speed of technological advancement is already highlighting the limitations of 5G, and its potentially short lifespan as new technologies are rendered obsolete faster. This fast-moving field is coupled with an ongoing and increasing funding into Research & Development (R&D) efforts by private corporations, to potentially commercialise on the surge in demand for ‘smarter’ cities’, This paper aims to chart the major directions and scope emerging dimensions inherent to 6G technology, including Digital Twins and Immersive Realities (XR) that, when applied to cities that are currently being equipped with digital infrastructural backbones, may have direct socio-economic impacts upon our lives while responding to the tenets of the Sustainable Development Goal 11. Looking at the future 6G technology this article considers the prospects of 6G, and its associated concepts, and its relations as they pertain to Future, Smart, Digital and Sustainable Cities.

Technical and Economic Feasibility Assessment of a Cloud-Enabled Traffic Video Analysis Framework

Computer vision techniques are expected to significantly improve the development of intelligent transportation systems (ITS), which are anticipated to be a key component of future Smart City frameworks. Powered by computer vision techniques, the conversion of existing traffic cameras into connected “smart sensors” called intelligent video analysis (IVA) systems has shown the great capability of producing insightful data to support ITS applications. However, developing such IVA systems for large-scale, real-time application deserves further study, as the current research efforts are focused more on model effectiveness instead of model efficiency. Therefore, we have introduced a real-time, large-scale, cloud-enabled traffic video analysis framework using the NVIDIA DeepStream and NVIDIA Metropolis. In this study, we have evaluated the technical and economic feasibility of our proposed framework to help traffic agency to build IVA systems more efficiently. Our study shows that the daily operating cost for our proposed framework on Google Cloud Platform is less than $0.14 per camera, and that, compared with manual inspections, proposed framework achieves an average vehicle-counting accuracy of 83.7% on sunny days.

Preface

Due to recent pandemic, the 2020 International Conference on Urban Construction and Management Engineering (ICUCME 2020) which was planned to be held in in Taiyuan, China was held virtually online during Oct. 16-18, 2020. The decision to hold the virtual conference was made in compliance with many restrictions and regulations that were imposed by countries around the globe. Such restrictions were made to minimize the risk of people contracting or spreading the COVID-19 through physical contact. There were 40 individuals who attended this on-line conference, represented many countries including New Zealand, Malaysia, India, Singapore, UK and China.ICUCME 2020 is to bring together innovative academics and industrial experts in the field of urban engineering, architectural planning, management engineering and environmental engineering to a common forum. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. An ideal platform for seeking global partners had been established.During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. In the second part, we invited three professors as our keynote speakers. A. Prof. Dr. Seyed Mohammadreza Ghadiri, from Malaysia University of Science and Technology, Malaysia, performed a speech on Smart Cities Vision of The Future. This speech discussed the key elements of future smart cities and addressed some questions: What does a smart city look like and how does it work? How do we benefit from the smart city? Data is the essential part of a smart city. It provides for designing and development of the intelligent applications for the city, but how is the data verified and what about data protection strategies? And then we had A. Prof. Mei-yung Leung from Department of Architecture and Civil Engineering, City University of Hong Kong. He talked about Value Management for Complex Projects along the Belt and Road Regions. In this presentation, critical factors applying VM in the complex projects along Belt and Road regions were shared and analyzed. Lastly, we were glad to invite A. Prof. Ahmad Safuan Bin A. Rashid, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia as our finale keynote speakers. He shared a speech on Engineering Characteristic and Chemical Properties of Bottom Ash Waste Material. Their insightful speeches had triggered heated discussion in the third session of the conference. Every participant praised this conference for disseminating useful and insightful knowledge.The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. Topics include but are not limited to the following areas: Urban development and construction, Management engineering and other related topics. All the papers have been through rigorous review and process to meet the requirements of International publication standard.We would like to acknowledge all of those who supported ICUCME 2020. The help and contribution of each individual and institution was instrumental in the success of the conference. In particular, we would like to thank the organizing committee for its valuable inputs in shaping the conference program and reviewing the submitted papers.We sincerely hope that the ICUCME 2020 turned out to be a forum for excellent discussions that enabled new ideas to come about, promoting collaborative research. We are sure that the proceedings will serve as an important research source of references and knowledge, which will lead to not only scientific and engineering findings but also new products and technologies.Committee of ICUCME 2020List of Committee member, Program Committee Chair, Organizing Committees, International Technical Program Committees are available in the pdf

Smart Building Surveillance System as Shared Sensory System for Localization of AGVs

The objective of this study is to extend the possibilities of robot localization in a known environment by using the pre-deployed infrastructure of a smart building. The proposed method demonstrates a concept of a Shared Sensory System for the automated guided vehicles (AGVs), when already existing camera hardware of a building can be utilized for position detection of marked devices. This approach extends surveillance cameras capabilities creating a general sensory system for localization of active (automated) or passive devices in a smart building. The application is presented using both simulations and experiments for a common corridor of a building. The advantages and disadvantages are stated. We analyze the impact of the captured frame’s resolution on the processing speed while also using multiple cameras to improve the accuracy of localization. The proposed methodology in which we use the surveillance cameras in a stand-alone way or in a support role for the AGVs to be localized in the environment has a huge potential utilization in the future smart buildings and cities. The available infrastructure is used to provide additional features for the building control unit, such as awareness of the position of the robots without the need to obtain this data directly from the robots, which would lower the cost of the robots themselves. On the other hand, the information about the location of a robot may be transferred bidirectionally between robots and the building control system to improve the overall safety and reliability of the system.

AN EFFICIENT APPROACH TO MANAGE DOMESTIC WASTEWATER IN SMART CITY

Abstract. The adoption of an ecological sanitation system, meeting the requirements hygienic and sanitary, constitutes a feasible and technically and economically acceptable solution in the future smart city. This new sanitation concept has the advantage of solving the problems of pathogens of human waste at source, thus offering the possibility of reusing them after treatment (recycling) in order to improve the standard of living of the population and protect the environment. The aim of this study is to evaluate the efficiency of a vertical Multi-Soil-Layering system (MSL) system to treat domestic wastewater under three hydraulic loading rates: 250 L/m2/day, 350 L/m2/day and 500 L/m2/day, in Moroccan conditions. To do this, a vertical MSL system measuring 20cm × 60cm × 78cm (L × W × H) was designed to treat domestic wastewater and his performance was investigated. The results showed high removal of organic matters and nutrients under the three hydraulic loads tested; the performance averages recorded are upper than 84 % for organic matters, 83.1 ± 7.2 % for ammonium and 72.4 ± 14.1 % for orthophosphate. The quality of the treated wastewater was evaluated according to Moroccan reject limit value. Consequently, this system could be considered an effective solution to be adopted for decentralized domestic wastewater treatment in Moroccan conditions.

The First Two Decades of Smart City Research from a Risk Perspective

Although they offer major advantages, smart cities present unprecedented risks and challenges. There are abundant discrete studies on risks related to smart cities; however, such risks have not been thoroughly understood to date. This paper is a systematic review that aims to identify the origin, trends, and categories of risks from previous studies on smart cities. This review includes 85 related articles published between 2000 and 2019. Through a thematic analysis, smart city risks were categorized into three main themes: organizational, social, and technological. The risks within the intersections of these themes were also grouped into (1) digital transformation, (2) socio-technical, and (3) corporate social responsibility. The results revealed that risk is a comparatively new topic in smart-city research and that little focus has been given to social risks. The findings indicated that studies from countries with a long history of smart cities tend to place greater emphasis on social risks. This study highlights the significance of smart city risks for researchers and practitioners, providing a solid direction for future smart-city research.

Reconfigurable cyber-physical system for critical infrastructure protection in smart cities via smart video-surveillance

Automated surveillance is essential for the protection of Critical Infrastructures (CIs) in future Smart Cities. The dynamic environments and bandwidth requirements demand systems that adapt themselves to react when events of interest occur. We present a reconfigurable Cyber Physical System for the protection of CIs using distributed cloud-edge smart video surveillance. Our local edge nodes perform people detection via Deep Learning. Processing is embedded in high performance SoCs (System-on-Chip) achieving real-time performance ($\approx$ 100 fps - frames per second) which enables efficiently managing video streams of more cameras source at lower frame rate. Cloud server gathers results from nodes to carry out biometric facial identification, tracking, and perimeter monitoring. A Quality and Resource Management module monitors data bandwidth and triggers reconfiguration adapting the transmitted video resolution. This also enables a flexible use of the network by multiple cameras while maintaining the accuracy of biometric identification. A real-world example shows a reduction of $\approx$ 75\% bandwidth use with respect to the no-reconfiguration scenario.

Towards Secure and Privacy-Preserving IoT Enabled Smart Home: Architecture and Experimental Study.

Internet of Things (IoT) technology is increasingly pervasive in all aspects of our life and its usage is anticipated to significantly increase in future Smart Cities to support their myriad of revolutionary applications. This paper introduces a new architecture that can support several IoT-enabled smart home use cases, with a specified level of security and privacy preservation. The security threats that may target such an architecture are highlighted along with the cryptographic algorithms that can prevent them. An experimental study is performed to provide more insights about the suitability of several lightweight cryptographic algorithms for use in securing the constrained IoT devices used in the proposed architecture. The obtained results showed that many modern lightweight symmetric cryptography algorithms, as CLEFIA and TRIVIUM, are optimized for hardware implementations and can consume up to 10 times more energy than the legacy techniques when they are implemented in software. Moreover, the experiments results highlight that CLEFIA significantly outperforms TRIVIUM under all of the investigated test cases, and the latter performs 100 times worse than the legacy cryptographic algorithms tested.

Overview of Energy Management and Leakage Control Systems for Smart Water Grids and Digital Water

Current and future smart cities are moving towards the zero-net energy use concept. To this end, the built environment should also be designed for efficient energy use and play a significant role in the production of such energy. At present, this is achieved by focusing on energy demand in buildings and to the renewable trade-off related to smart power grids. However, urban water distribution systems constantly carry an excess of hydraulic energy that can potentially be recovered to produce electricity. This paper presents a comprehensive review of current strategies for energy production by reviewing the state-of-the-art of smart water systems. New technologies (such as cyber-physical systems, digital twins, blockchain) and new methodologies (network dynamics, geometric deep learning) associated with digital water are also discussed. The paper then focuses on modelling the installation of both micro-turbines and pumps as turbines, instead of/together with pressure reduction valves, to further demonstrate the energy-recovery methods which will enable water network partitioning into district metered areas. The associated benefits on leakage control, as a source of energy, and for contributing to overall network resilience are also highlighted. The paper concludes by presenting future research directions. Notably, digital water is proposed as the main research and operational direction for current and future Water Distribution Systems (WDS) and as a holistic, data-centred framework for the operation and management of water networks.

Multi-objective evolutionary optimization with genetic algorithm for the design of off-grid PV-wind-battery-diesel system

With the increasing hazard to the environment and progressions in renewable energy technologies, hybrid renewable energy systems can meet the energy demand. Total dependability can be attained by adding battery banks to hybrid systems. This paper aims to optimally design a multi-source grid isolated hybrid generation system for future smart cities in the state of Tamil Nadu, India. This off-grid power generation consists of wind turbine generators, photovoltaic panels, inverters, diesel generators, and batteries. The design intents at minimizing Net Present Cost, Unmet Load, and CO2 emissions which are conventionally contradictory to each other. This paper analyzes the optimal off-grid combination of components and control strategies, utilizing improved Hybrid Optimization using the Genetic Algorithm. The results obtained portrays that a mix of hybrid renewable energy generators at off-grid locations without diesel generators can be a cost-effective choice of new smart cities, and it is sustainable, environmentally viable, and techno-economically feasible. Subvention is imperative to take on the large-scale system due to the high capital cost.

A survey on physical unclonable function (PUF)-based security solutions for Internet of Things

The vast areas of applications for IoTs in future smart cities, smart transportation systems, and so on represent a thriving surface for several security attacks with economic, environmental and societal impacts. This survey paper presents a review of the security challenges of emerging IoT networks and discusses some of the attacks and their countermeasures based on different domains in IoT networks. Most conventional solutions for IoT networks are adopted from communication networks while noting the particular characteristics of IoT networks such as the nodes quantity, heterogeneity, and the limited resources of the nodes, these conventional security methods are not adequate. One challenge towards utilizing common secret key-based cryptographic methods in large-scale IoTs is the problem of secret key generation, distribution, and storage and protecting these secret keys from physical attacks. Physically unclonable functions (PUFs) can be utilized as a possible hardware remedy for identification and authentication in IoTs. Since PUFs extract the unique hardware characteristics, they potentially offer an affordable and practical solution for secret key generation. However, several barriers limit the PUFs’ applications for key generation purposes. We discuss the advantages of PUF-based key generation methods, and we present a survey of state-of-the-art techniques in this domain. We also present a proof-of-concept PUF-based solution for secret key generation using resistive random-access memories (ReRAM) embedded in IoTs.

Deep neural network based anomaly detection in Internet of Things network traffic tracking for the applications of future smart cities

AbstractAn anomaly exposure system's foremost objective is to categorize the behavior of the system into normal and untruthful actions. To estimate the possible incidents, the administrators of smart cities have to apply anomaly detection engines to avert data from being jeopardized by errors or attacks. This article aims to propose a novel deep learning‐based framework with a dense random neural network approach for distinguishing and classifying anomaly from normal behaviors based on the type of attack in the Internet of Things. Machine learning algorithms have the improbability to explore the performance, compared with deep learning models. Distinctively, the examination of deep learning neural network architectures achieved enhanced computation performance and deliver desired results for categorical attacks. This article focuses on the complete study of experimentation performance and evaluations on deep learning neural network architecture for the recognition of seven categorical attacks found in the Distributed Smart Space Orchestration System traffic traces data set. The empirical results of the simulation model report that deep neural network architecture performs well through noticeable improvement in most of the categorical attack.

Federated learning based caching in fog computing for future smart cities

Edge devices in the Internet of Things (IoT) networks are responsible for the continuous generation and communication of massive chunks of transient data to the fog devices for data processing. However, resources at the fog nodes are limited. Therefore, objective of the work is efficient caching, which is achieved using Federated Learning (FL), where the data used for learning is not gathered centrally but remains where it is produced. Therefore, the heavy transmission of the data to the fog nodes for learning is not required. Simulation results depict the advantages of using this approach over other centralized approaches.

Achieve Efficient and Privacy-Preserving Disease Risk Assessment Over Multi-Outsourced Vertical Datasets

It is believed that online disease risk assessment system has great potential to alleviate the medical treatment problems for the future smart city and communities, as it can excavate disease risk factors from a large number of patient features, provide diagnostic references for doctors, and save medical treatment time for patients. However, the flourish of online disease risk assessment service still faces severe challenges including information privacy and security. In this article, based on the naïve Bayesian classification, we propose an effi <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</u> ient and priv <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u> cy-prese <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</u> ving dis <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</u> ase <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</u> isk assessment scheme over multi-outsourced vertical datasets, named CARER. With CARER, the e-healthcare provider can securely train a disease risk predication model over vertically distributed medical data from multiple medical centers (i.e., hospitals), and provide privacy-preserving disease risk predication services for users (i.e., patients and doctors). During the model training and disease risk prediction phases, all sensitive data are operated over ciphertexts without decryption. As a result, the private information of medical centers, e-healthcare provider, and users can be well protected. Detailed security analysis shows that CARER can resist various known security threats. In addition, we evaluate the performance of CARER with real medical datasets, and the results demonstrate that CARER is efficient.

Smart cities in collaboration with the internet of things

The use of the Internet has Reached a point in the world in Which it has Become essential in everyday life, the need to Have information at hand in the shortest possible time has generated a technological revolution That incurs the constant connection to this tool, from our Personal life to the same objects That we use in daily life, creating a need to check what surrounds us to Improve our quality of life, reason for the birth of the Internet of Things (IoT, for acronym in English), as well as the convergence of our environment through the creation with Technology of smart cities (Smart City in English). In view of the above, this article addresses concepts about the future of smart cities in collaboration with the Internet of things, the advantages and Disadvantages of these, their comparison, reception, adaptability.