Future Smart Cities Research Articles

ISSUES AND WAY FORWARD FOR THE SMART SUSTAINABLE CITIES AND COMMUNITIES STANDARDS: THE MALAYSIAN CASE IN THE POST-COVID-19 ERA

Governing a city’s development with the use of standards started relatively recently, in the mid-2010s. However, the issues of such city standards in systematically governing future smart cities remains largely unknown under the digital infrastructural stress of the post-COVID-19 era. Therefore, this paper aims to examine the issues and directions in developing the Malaysian smart sustainable cities and communities standards that suit the post-COVID-19 era. This study applied the multiple case study method to compare the international literatures and the local smart city webinars. The results showed that smart city standards were welcomed by policymakers and practitioners, although issues such as learning, connectivity, and citizenship rationale need to be addressed. More focus should be put on how humans relearn and responsibly participate in the post-COVID-19 cyber-physical ecosystem in order to create a healthy and sustainable digital-based society. This paper has contributed as one of the first researches examining the role of smart city standards in Malaysia.

Research on recognition algorithm of impact vibration based on HOG feature of time–frequency spectrum

The time–frequency spectrum of the vibration signal obtained based on the time–frequency transformation algorithm can fully reflect the energy distribution at any time–frequency coordinate. But this characteristic is not easy to be insight and generalized by the human eye, especially in the era of big data, in the face of massive data and rapid processing. During the research, we found that this information can be clearly expressed in the histogram of oriented gradient (HOG) feature of the time–frequency spectrum. Therefore, the time–frequency spectrum support vector machine classifier based on the HOG feature of the vibration signal has considerable feasibility. This article had conducted in-depth research on this idea, determined the advantages of wavelet time–frequency spectrum for signal recognition, and further selected wavelet basis and kernel function. A comprehensive test of the HOG parameters had finally achieved a good recognition effect. The comprehensive recognition accuracy of the algorithm for the impact and vibration signals collected in this paper was stable at about 96%. The research results will be applied to the future smart city vibration monitoring system. On the other hand, it may provide a new idea to improve the accuracy of the current battlefield target recognition system.

THE FUTURE OF SMART CITIES

IoT, big data analytics, and machine learning advancements have made the concept of a smart city a reality. The goal of a smart city, as we all know, is to give efficient answers to its residents using modern technology and data analytics collected by sensors. The idea of a smart city was something SF for many people in the 20th century, that was anyway pictured just in the popular media. Cities are becoming smarter not just in terms of how we can automate regular operations for individual people, buildings, and traffic systems, but also in terms of how we can monitor, comprehend, analyze, and design the city in real time to increase efficiency, equity, and quality of life for its population. A smart city goes beyond utilizing digital technology to improve resource efficiency and reduce pollution. It entails improved urban transportation networks, updated water and waste disposal facilities, and more energy-efficient lighting and heating systems. It also entails a more involved and responsive local government, safer public areas, and addressing the needs of older people. In this paper we will approach the actual smart city, what is it today; how they developed in recent years, the domains where is implemented (traffic management, healthcare, and public safety for example) and the future of smart cities in the whole world.

Multi-objective risk-constrained optimal performance of hydrogen-based multi energy systems for future sustainable societies

Hydrogen is one of the leading energy sources under special consideration due to its sustainability and technological development. The main concept of integrated energy system is applied in this article. The goal is to maintain a coordination between hydrogen cycle where hydrogen is produced and converted with renewable energy (RE). Three energy storage for charging/discharging hydrogen, hot and cold water are employed enhance the energy efficiency. The demand-side energy system could rely on this combination that enables the increase in wind and solar energy utilization and uses it to generate hydrogen in future smart cities. This paper uses a scenario-based stochastic optimization to model the associated uncertainties. The epsilon-constraint and max-min fuzzy methods are used as multi-objective approach to satisfy environmental and economic goals, simultaneously. To analyze the associated risk imposed by multiple uncertain parameters, the downside risk constraint (DRC) is implemented to render several risk-averse strategies to the decision-maker based on various constraint level. The results show that the final solution in risk neutral strategy satisfies both emission and operation costs. The ultimate associated risk in conservative strategy will tend to zero at the 4.2% operation cost increment and 3% emission reduction.

Smart city and spatial configuration: assessing accessibility and intelligibility to increase mobility in the George Town heritage site, Malaysia

PurposeThe emerging concept of smart city is known to aim at sustainable urban development. One of the requirements for a smart city is to address accessibility inequalities. This study aims to investigate the accessibility level issues in urban transformation before and after combining different street networks for Penang, Malaysia, as a case study to reveal greater insight and helpful information into mobility and accessibility inequalities for future smart city planning.Design/methodology/approachUsing DepthmapX software, two main quantitative methodologies of space syntax, namely, spatial integration accessibility (SIA) and angular segment analysis by metric distance (ASDMA), are employed to analyse the level of accessibility for the main streets of George Town site before and after combination with contemporary networks. Integration, choice and entropy values were calculated for the study analysis.FindingsResults revealed the implications of combining old irregular gridiron structures with the existing planned grid structures. George Town seems to have gained a higher capacity for pedestrian accessibility; however, vehicle accessibility has lost its capacity. Findings further suggest that a combination of irregular structure and grid structure is essential for urban growth in similar historical contexts to improve accessibility and address mobility inequalities.Originality/valueThe study concludes by highlighting the importance of the analysis of street structure transformation to predict consequences and promote the potential to reduce current inequalities in vehicle accessibility.

Understanding citizen perceptions of AI in the smart city

Artificial intelligence (AI) is embedded in a wide variety of Smart City applications and infrastructures, often without the citizens being aware of the nature of their “intelligence”. AI can affect citizens’ lives concretely, and thus, there may be uncertainty, concerns, or even fears related to AI. To build acceptable futures of Smart Cities with AI-enabled functionalities, the Human-Centered AI (HCAI) approach offers a relevant framework for understanding citizen perceptions. However, only a few studies have focused on clarifying the citizen perceptions of AI in the context of smart city research. To address this gap, we conducted a two-phased study. In the pre-study, we explored citizen perceptions and experiences of AI with a short survey (N = 91). Second, scenario-based interviews (N = 7) were utilized to gain in-depth insights of citizen perceptions of AI in the Smart City context. Five central themes were recognized: (1) I don’t like them monitoring me, (2) I want maximum gain for minimum effort, (3) I don’t want AI to mimic people, (4) I’ll avoid using AI if I consider the risk too high, and (5) I don’t need to be concerned about AI. These offer an idea of human-centered requirements worth considering while designing AI applications for future Smart Cities.

Investigating Media-User Interaction for Public Play Space in a Smart City

The problem of focusing only on the efficiency of an ICTs’ digital convergence in technology-oriented smart city construction has been raised. To address this problem, Plan Smart City Comprehensive Plan is in progress, excluding play spaces in public spaces where the city and users communicate directly or indirectly. In addition, when looking at Christopher Alexander’s 253 pattern languages, which many scholars and experts consider as a study guide for urban planning projects, there is no design alternative for ICTs’ digital convergence for future smart cities. Therefore, in this study, we propose a 4th plan model for ICTs’ future smart city development regarding digital technology and a place-oriented digilog strategic plan. This model proposal is applied to an actual project where the user and the space can interact based on the user’s behavior analysis using the keywords of participation, sharing, and cooperation in the public play space. This study aims to verify the rational method of the ICTs’ smart city Future 4th plan model alternative. There is a strategic plan for ICTs’ participatory media user interaction in a public play space in which: 1. the way people behave in the space; 2. the way people interact with the space; 3. the way people accept the actions of others for entertainment and enjoyment. This study can contribute as a strategic plan for ICTs’ participatory media-user interaction in a public play space; it can contribute to the rational design of the presentation of digilog strategic planning.

Promises of Interdependent Power and Energy Systems for Future Smart Cities

Promises of Interdependent Power and Energy Systems for Future Smart Cities

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

Homes are the building block of cities and societies and therefore smart homes are critical to establishing smart living and are expected to play a key role in enabling smart, sustainable cities and societies. The current literature on smart homes has mainly focused on developing smart functions for homes such as security and ambiance management. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, and the roles of smart homes that will serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public, using over a hundred thousand research papers and nearly a million tweets. We developed a methodology using deep learning, natural language processing (NLP), and big data analytics methods (BERT and other machine learning methods) and applied it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100 s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.

Management and Regulation of Drone Operation in Urban Environment: A Case Study

With the exponential growth of numerous drone operations ranging from infrastructure monitoring to even package delivery services, the laws and privacy regarding the use of drones in the urban planning context play an essential role in future smart cities. This study provides a comprehensive survey of the regulation of drone application and drone management systems, including a comparison of existing rules, management methods, and guidelines in drone operation to guarantee the safety and security of people, property, and environment. Evaluating existing regulations and laws practiced worldwide will assist in designing drone management and regulation. In Vietnam, the current rules can manage and regulate general guidelines of drone operations based on prohibited, restricted, and controlled areas within the urban context. The legislation, however, is unclear as to how it regulates smaller civilian unmanned aircraft used in the country. In the legal aspect, the potential consequences consist of the inefficiency of compensation responsibility, the violation of drone regulations, and information insecurity.

Wireless Self-Powered High-Performance Integrated Nanostructured-Gas-Sensor Network for Future Smart Homes

The accelerated evolution of communication platforms including Internet of Things (IoT) and the 5th generation (5G) wireless communication network makes it possible to build intelligent gas sensor networks to monitor the chemical safety of our surroundings and personal health in real time. However, this application scenario requires a very challenging combination of characteristics of gas sensors including small formfactor, low-cost, ultra-low power consumption, superior sensitivity, and high intelligence. Herein, we demonstrate self-powered integrated nanostructured-gas-sensor (SINGOR) systems and a wirelessly connected SINGOR network for the first time. The SINGOR features ultra-high sensitivity to H2, formaldehyde, toluene, and acetone with the record low limits of detection (LOD) of 10 ppb, 2 ppb, 1 ppb and 1 ppb, respectively, obtained under room temperature sensor operation. Therefore, ultra-low power consumption of 68.6 μW at sensor level and 1.71 mW at the system level has been achieved. As the result, an individual SINGOR system can be self-driven by indoor light with a Si solar cell. Furthermore, each SINGOR consists of an array of nanostructured sensors powered by machine learning algorithm and thus a SINGOR has the capability of gas pattern recognition and classification. And multiple SINGOR systems are wirelessly connected together to form a sensor network for smart home application demonstrations. Intriguingly, the sensor network has successfully demonstrated flammable gas leakage detection and alarm function when they are deployed in multiple rooms. And when the SINGOR network is deployed in one single room, it can achieve gas leakage localization with satisfactory precision. These successes open up the possibility of using nanostructured-gas-sensor network for wide range applications including smart home, smart building and future smart city.

Future of Smart Cities: The Role of Machine Learning and Artificial Intelligence

The goals of "smart cities" include relieving the burden of growing urbanisation, cutting down on energy use, protecting the environment, boosting the local economy and people's standard of living, and facilitating wider access to and use of cutting-edge Information and Communication Technologies (ICT). In smart cities, ICT is essential for policymaking, decision making, plan execution, and the delivery of useful services. The primary goal of this analysis is to investigate the part that AI and machine learning play. Examples of ed tech include Deep Reinforcement Learning (DRL) and Machine Learning (ML). In a complicated smart city setting, the aforementioned methods can be used to develop the best possible rules. Smart transportation, cyber-security, energy-efficient usage of smart grids (SG), efficient use of Unmanned Aerial Vehicles (UAVs) to guarantee the best 5G and beyond 5G (B5G) communications, and a smart health monitoring are all discussed in length in this paper. Finally, we discuss the research challenges that have yet to be met and potential future research directions that could bring the concept of a "smart city" closer to fruition.

Realistic representation of city street-level human thermal stress via a new urban climate-human coupling system

Urban overheating aggravated by climate change and rapid urbanization poses a severe threat to thermal health of urban residents. To more realistically represent street-level heat stress, we propose a new urban climate-human coupling system by integrating an advanced urban canopy model (UCM) with a new human-environment adaptive thermal stress (HEATS) module. The coupled UCM-HEATS system features a state-of-the-art solution to complicated human-street radiative exchanges and incorporates dynamic human thermoregulatory responses to microclimatic changes. The UCM-HEATS system was evaluated in a typical hot and humid city, Hong Kong, and then applied to investigate street-level thermal stress in various urban settings and under different personal conditions. By explicitly resolving shading effects of buildings and trees on human radiation budgets, our study emphasizes the marked effectiveness of active shade management using green and gray infrastructure on daytime heat mitigation, proposing a “right shade, right place, right time” paradigm for regulating important street canyon geometries (building height, road width, and tree crown width) and orientations. Additionally, human evaporative heat dissipation can be hindered by urban moisture islands and wind impediments; thus, a detailed urban ventilation strategy is suggested considering different temperature-humidity combinations. For personal heat protection, we identified an evident cooling effect of high-albedo clothing and a thermal-comfort-optimal walking speed. Special attention is paid to heat-vulnerable groups, especially older people who suffer from notably higher heat risks during pandemics with facemask-induced heat burden. Bridging urban climate and human ergonomics, this study aims to advance human-centric urban design toward future smart, resilient, and inclusive cities.

Communication, sensing, computing and energy harvesting in smart cities

A smart city provides diverse services based on real-time data obtained from different devices deployed in urban areas. These devices are largely battery-powered and widely placed. Therefore, providing continuous energy to these devices and ensuring their efficient sensing and communications are critical for the wide deployment of smart cities. To achieve frequent and effective data exchange, advanced enabling information and communication technology (ICT) infrastructure is in urgent demand. An ideal network in future smart cities should be capable of sensing the physical environment and intelligently mapping the digital world. Therefore, in this paper, we propose design guidelines on how to integrate communications with sensing, computing and/or energy harvesting in the context of smart cities, aiming to offer research insights on developing integrated communications, sensing, computing and energy harvesting (ICSCE) for promoting the development ICT infrastructure in smart cities. To put these four pillars of smart cities together and to take advantage of ever-increasing artificial intelligence (AI) technologies, the authors propose a promising AI-enabled ICSCE architecture by leveraging the digital twin network. The proposed architecture models the physical deep neural network-aided ICSCE system in a virtual space, where offline training is performed by using the collected real-time data from the environment and physical devices.

Phase change material coupled building envelope for thermal comfort and energy-saving: Effect of natural night ventilation under hot climate

Incorporating phase change material (PCM) into buildings in hot climates is an excellent strategy for better thermal comfort and energy-saving in future smart cities. Nevertheless, PCM elements suffer from adverse temperature behaviour at night due to the dissipation of stored diurnal heat. Night ventilation has been proposed as a promising solution and clean strategy for decreasing indoor building temperature at night and increasing PCM benefits in the following cycle. In this study, the effect of the natural night ventilation (NNV) period on the thermal performance of a room-integrated PCM is investigated experimentally under hot summer conditions in Iraq. Six NNV periods (with 1 h increment) are studied for six consecutive days in terms of average indoor and operative temperature reduction. Moreover, the work is extended to study the average heat gain difference in each day cycle to show the contribution of PCM to energy-saving. The results showed a slight enhancement in the average indoor air temperature of the PCM room compared with another identical no-PCM room regardless of the NNV period due to high outdoor ambient temperature at night. However, NNV for 4 h can reduce the average indoor air temperature by 28.6% compared with 1 h of NNV, whereas a slight extra reduction was achieved for 5 and 6 h. Besides, NNV slightly affected the operative temperature at night against no impact during the day, which was more influenced by the solar radiation and high diurnal ambient temperature. The results further revealed that a total average heat gain difference of 63.1–87.9 W was achieved, in which the roof contributed by more than 44% in each cycle. • A PCM coupled building envelope is studied experimentally under severe hot climate. • The effect of NNV on PCM behaviour is evaluated considering the AITR and OTR. • Four-night hours of NNV could lower the indoor temperature of the PCM room to a limit. • Total AHGD of PCM room decreased by 63.1–87.9 W, and the roof contributed by 44%. • Diurnal ambient temperature and solar radiation had influenced the daily AHGR more than NNV.

Sustainable Development of Smart City Concept Linked to Limited Resources Abroad and in Slovakia

Population growth in the urban environment generates higher consumption of limited resources. Following the results of our own sociological research, this paper aims to identify issues in the field of Smart City sustainable development and identify the specific limited resource that needs to be managed sustainably in the Smart City concept abroad and in Slovakia. The main findings in Slovakia confirm the occurrence of insufficient awareness, low state aid, limited funding. Within the sample of global Smart Cities involved in the survey, the issue of insufficient funding was identified in particular. Among the limited sources, both foreign and Slovak respondents consider water sources to be of critical importance. The ambition of the research is to improve the understanding of the management of the limited resources in the concept of future Smart Cities in Slovakia and to suggest solutions to the issues as recommendations presented in the Discussion of this paper.

Blockchain-Based Privacy-Preserving and Sustainable Data Query Service Over 5G-VANETs

Intelligent Transport Systems (ITSs) play an important role in future smart city design to improve traffic safety and traffic congestion by sharing data collected by vehicles. For sharing the traffic data with other vehicles, the vehicular sensory data are usually uploaded to the cloud server. However, existing data sharing systems for VANETs cannot provide selective data with sufficient privacy protection. Moreover, some schemes also cannot ensure stable data accessibility and the integrity of retrieved data. On the other hand, with the improvements such as lower latency, higher capacity, and increased bandwidth, 5G technology brings more possibilities to future applications. The join of the software-defined networks (SDNs) also offers efficient and effective network management. This paper proposes a primitive vehicular communication system named blockchain-based privacy-preserving and sustainable data query service. The proposed scheme is designed to realize stable data accessibility by leveraging smart contracts and blockchain oracle. With the help of 5G technology and P2P file-sharing system, InterPlanetary File System (IPFS), the proposed scheme aims to support video downloading files with searchable capability and fairness. An incentive token mechanism is also equipped. The merit of auditability is ensured by Ethereum blockchain platform to support the accountability. Besides, we also evaluate its networking performance via SUMO and NS-3 simulators. Our simulation results show that the request-response delay of BPSDQS is less than existing blockchain-based proxy re-encryption (PRE) scheme. Our simulation results also showed that the average request-response delay in our scheme can saving up to 98%.

Research on Intelligent Management Solutions for Sustainable, Low-Carbon Future Smart Cities and Industrial Parks in China

China is a developed country promoting intelligent services, which can increase the country's sustainability appropriately. This is done by using innovative technologies to reduce the carbon footprints in the country. The technical innovations have helped maintain low-carbon for the country's future development. Intelligent technologies in the country help manage renewable energy by making environmental transformation easier (Darda et al., 2019). This research article will help find different management solutions for sustainable low-carbon for future smart cities and industrial parks in China. Moreover, this article will help find an in-depth review of China's policies to manage the future of the industrial parks.

Trends and Emerging Technologies for the Development of Electric Vehicles

In response to severe environmental and energy crises, the world is increasingly focusing on electric vehicles (EVs) and related emerging technologies. Emerging technologies for EVs have great potential to accelerate the development of smart and sustainable transportation and help build future smart cities. This paper reviews new trends and emerging EV technologies, including wireless charging, smart power distribution, vehicle-to-home (V2H) and vehicle-to-grid (V2G) systems, connected vehicles, and autonomous driving. The opportunities, challenges, and prospects for emerging EV technologies are systematically discussed. The successful commercialization development cases of emerging EV technologies worldwide are provided. This review serves as a reference and guide for future technological development and commercialization of EVs and offers perspectives and recommendations on future smart transportation.

Smart city re-imagined: City planning and GeoAI in the age of big data

This paper aims to engage with the ongoing debates on the role of planning in future smart cities, to make a case for a reconceptualization of the technocentric notion of the smart city, and to elevate the position of city planning within the smart-city discourse. The central argument made is that the smart city could exploit the synergies between city planning and three techno-scientific domains including Big Data, Geographic Information Science and Systems, and Data Science—which collectively constitute an emerging field known as Geospatial Artificial Intelligence (GeoAI)— to meet four overarching policy goals: 1) to enhance the efficiency of urban services and functions; 2) to improve quality of life for all urban citizens; 3) to address the pressing societal, ecological and economic challenges that could plague urban systems on different levels; and, 4) to contribute to the production of spatial data, information and knowledge on human-urban dynamics. In addition, the paper defines a human-centered conceptual framework illustrating how the cross-pollination between city planning and the three techno-scientific fields could enhance the planning practice and accomplish the smart-city policy goals. The methodology employed in this study entails a systematic review of the literature. In addition to discussing the latest achievements as well as the progress made on the nexus of city planning and GeoAI, the paper also highlights the barriers to the application of GeoAI in the planning, design and management of smart cities and identifies potential avenues for future research.