Areas Of Smart Cities Research Articles

Contextual visual and motion salient fusion framework for action recognition in dark environments

Infrared (IR) human action recognition (AR) exhibits resilience against shifting illumination conditions, changes in appearance, and shadows. It has valuable applications in numerous areas of future sustainable and smart cities including robotics, intelligent systems, security, and transportation. However, current IR-based recognition approaches predominantly concentrate on spatial or local temporal information and often overlook the potential value of global temporal patterns. This oversight can lead to incomplete representations of body part movements and prevent accurate optimization of a network. Therefore, a contextual-motion coalescence network (CMCNet) is proposed that operates in a streamlined and end-to-end manner for robust action representation in darkness in a near-infrared (NIR) setting. Initially, data are preprocessed to separate foreground, normalized, and resized. The framework employs two parallel modules: the contextual visual features learning module (CVFLM) for local feature extraction, and the temporal optical flow learning module (TOFLM) for acquiring motion dynamics. These modules focus on action-relevant regions used shift window-based operations to ensure accurate interpretation of motion information. The coalescence block harmoniously integrates the contextual and motion features within a unified framework. Finally, the temporal decoder module discriminatively identifies the boundaries of the action sequence. This sequence of steps ensures the synergistic optimization of both CVFLM and TOFLM and thorough competent feature extraction for precise AR. Evaluations of CMCNet are carried out on publicly available datasets, InfAR and NTURGB-D, where superior performance is achieved. Our model yields the highest average precision of 89% and 85% on these datasets, respectively, representing an improvement of 2.25% (on InfAR) compared to conventional methods operating at spatial and optical flow levels which underscores its efficacy.

Smart life and sustainable development: a comparative analysis on energy and water efficiency in China and the EU

Smart life relies on huge volumes of data analysis, which makes data centers become important infrastructure in smart city areas. Nowadays, data centers are constructed in many countries and have become increasingly large electricity consumers. The consumption of electricity is caused not only by the servers of data centers but also by the cooling systems. Meanwhile, data centers also demand water - cooling methods, which result in water consumption. As for sustainable development, water and energy consumption are huge challenges. Laws and rules are necessary for utilizing efficiently relevant sources. This paper will analyze China and the European Union (EU) as two examples of jurisdictions to compare how the governments regulate the construction of data centers to implement the thrift of electricity and water. In China, provinces and cities established diverse regulations based on their different natural and climate conditions, thus there is not a uniform model for the implementation in the country. In the EU, the amendment of Energy Efficiency Directive seeks to establish common policies. The difference of rules in these two jurisdictions reflects that China and the EU have their own principles and objectives: China attempts to balance the demand of developing smart city infrastructures and the consumption on natural resources, but the EU has strong ambition on low carbon emission in the whole Union. However, the two jurisdictions still have a common goal to maximize the efficiency of water and electricity consumption which is a fundamental issue for accelerating the transition towards sustainability.

TRANSPORT AND LOGISTIC SYSTEMS IN THE SMART CITY CONCEPT

Topicality. The impact of a number of factors on climate change can be defined as twofold. Firstly, by reducing the number of pollutants responsible for global warming, and secondly, by increasing the resilience of systems (economic, environmental, social) to the vulnerability of these factors. A huge number of scientific and professional developments, strategic documents, programmes and implementation plans are devoted to these issues. Nevertheless, a tangible effect of mitigating the impact of negative environmental factors, of which transport and logistics systems (TLS) play a leading role, including TLS of urban areas, can only be achieved through an integrated approach, combining the cooperation of various stakeholders with different public interests and goals.Aim and tasks. The purpose of the study is to establish priorities and directions for the formation of new type of transport and logistics systems in the concept of a smart cityMaterials and Methods. To carry out the research, the method of processing documented data from primary sources was used – scientific publications, expert opinions, documents of municipal authorities on this issue.Research results. The peculiarity of the concept of sustainable development lies in the contradiction of its defining postulates to traditional economic mechanisms of unlimited economic growth, maximum state regulation, and profit-making by any means, without coordinating their strategies with the needs of the environment that these urban agglomerations use. It is worth noting that the vast majority of scholars and decision-makers on urban development strategies adhere to the concept of a "smart" city in terms of its intellectual provision with technologies, use algorithms, advanced digital infrastructure, etc. The economic sustainability of the transport system should aim to plan transport projects, resource consumption, etc. in a way that promotes economic growth in the long term, as the increase in the number of smart cities, as a resource-intensive and time-consuming process, is one of the mechanisms for accelerating the modernisation of the national economy as a whole. The concept of expanding the area of smart cities contributes to the expansion of domestic consumption in the region, modernisation of industry, and coordination of economic and social activities between regions.Conclusion. Taking as a basis the principles of sustainable development of transport and logistics systems of cities on the basis of the introduction of green logistics can reduce numerous environmental problems that have become a consequence of industrial modernization and globalization, and ensure the reduction of external environmental effects by balancing environmental, social and economic goals by transport and logistics enterprises.

Smart City 4.0 development as a solution for NETZero economy

Purpose: Research of determinands Smart City development in NETZero Economy environment. Design/methodology/approach: This research shows the theory of 4T potentials, covering areas like technology, trust, talent and tolerance. Findings: This study attempts to identify results of 4T implementation in chosen cities of GZM 1Metropoly to identify, acquire, and develop Smart City areas and possibly synergy. Research limitations/implications: The author tries to identify by the research of local politics the innovative potential of a learning city and to diagnose the innovative potential of cities in the context of an energy efficiency, entrepreneurship, innovativeness of residents, and entities that support innovativeness. The problem is lack of implemented the politics of evelopment in research area in the cities. Practical implications: The author shows the examples that the local governments of selected cities are not prepared to use the synergies resulting from the possibilities offered by Smart City in the technology areas. Social implications: The author shows the examples that the local governments of selected cities are not prepared to use the synergies resulting from the possibilities offered by Smart City in the Social like Trust, Trust or Tolerance. Originality/value: Using 4T Theory in research because this study attempts to identify results of 4T implementation in chosen cities of GZM Metropoly to identify, acquire, and develop Smart City areas and possibly synergy in NETZero Economy development. Keywords: city management, 4T capitals, smart city, NetZero, energy efficiency. Category of the paper: Research Paper.

Anteseden Niat Kewirausahaan Berkelanjutan Gen Z Kawasan Smart City Semarang: Apakah Teknologi dan Pemerintah Daerah Berperan?

The UN Agenda for Sustainable Development 2030 focuses on entrepreneurship as a solution to turn ideas into action in building smart cities. Research states that entrepreneurship is crucial in creating sustainable companies in growing cities. Smart City is becoming a center for innovation and data technology to improve city services. Semarang City, as the center of economy and education in Indonesia, has implemented the Smart City concept since 2013. The rapid development of this city, together with the demographic bonus of Generation Z, supports the implementation of technological solutions in support of an adaptive and sustainable Smart City concept. This study aims to investigate the influence of urban entrepreneurship and entrepreneurship education on the sustainable entrepreneurial intentions of Gen Z in the Smart City Area, in this case study Semarang City, by considering the moderator of the role of technology and local government support. This study proposes six hypotheses according to the proposed model of sustainable entrepreneurship in Smart City areas with moderation of business technology and government support. This study chose a survey-based quantitative approach on 250 local Semarang students, and the response data was analyzed using the SEM-PLS technique. The results showed that urban entrepreneurship and Entrepreneurship Education significantly positively affect the sustainable entrepreneurial intentions of the Smart City area.Furthermore, it is proven that business technology and local government support moderate relations between urban entrepreneurship and Entrepreneurship Education with the intention of sustainable entrepreneurship in the Semarang Smart City area. The study recommends the integration of the concept of entrepreneurship in the college curriculum and the establishment of partnerships between universities, industry, and government in Semarang City. The government must expand internet connectivity, provide training programs for entrepreneurs, utilize technology in city infrastructure, and collaborate with educational institutions and industry for inclusive and innovative economic growth.

Information Security Applications in Smart Cities: A Bibliometric Analysis of Emerging Research

This paper aims to analyze the intellectual structure and research fronts in application information security in smart cities to identify research boundaries, trends, and new opportunities in the area. It applies bibliometric analyses to identify the main authors and their influences on information security and the smart city area. Moreover, this analysis focuses on journals indexed in Scopus databases. The results indicate that there is an opportunity for further advances in the adoption of information security policies in government institutions. Moreover, the production indicators presented herein are useful for the planning and implementation of information security policies and the knowledge of the scientific community about smart cities. The bibliometric analysis provides support for the visualization of the leading research technical collaboration networks among authors, co-authors, countries, and research areas. The methodology offers a broader view of the application information security in smart city areas and makes it possible to assist new research that may contribute to further advances. The smart cities topic has been receiving much attention in recent years, but to the best of our knowledge, there is no research on reporting new possibilities for advances. Therefore, this article may contribute to an emerging body of literature that explores the nature of application information security and smart cities research productivity to assist researchers in better understanding the current emerging of the area.

OPTIMIZATION OF PUBLIC TRANSPORTATION NOSES IN THE IMPLEMENTATION OF ELECTRIC VEHICLE-BASED GREEN INFRASTRUCTURE TO REALIZE A GREEN CITY IN THE NUSANTARA CAPITAL REGION THROUGH IMPLEMENTATION OF RENEWABLE ENERGY

Law Number 3 of 2022 is the legal basis for moving the National Capital from DKI Jakarta to Sepaku, East Kalimantan, which is called the Capital City of the Archipelago (IKN). To prevent serious emissions cases from recurring in the capital city of Jakarta, the low emission zone concept needs to be implemented to achieve a smart and green city area in IKN. Community mobility in IKN is directed at 80% to use public transportation with an access time of 10 minutes to public transportation nodes, so that with the large area of ​​IKN it is very necessary to optimize the development of public transportation nodes. This research aims to determine the use of the type of electric vehicle with the lowest emissions and determine the optimal number of bus terminal mapping, so that it can reduce emissions due to transportation activities and create financial savings in the process of installing solar panels as a means of converting renewable energy sources at each bus terminal in the IKN area. . This research method was carried out by studying a literature review regarding electric vehicles and using the set covering problem method in determining the optimal number of bus terminals, as well as using the interview method to obtain primary data. BEV type electric vehicles are most suitable for use in IKN, because they emit fewer emissions than other types. In creating optimization, there are six bus terminal construction locations that can serve other areas in IKN.

Smart Dustbin

The production of waste is rising as urbanisation spreads quickly. Waste management is an important factor to take into account in public areas when waste overflows from the bins and may cause various diseases. The goal of the current effort is to create a smart dustbin model that can be successfully deployed in public areas of smart cities. The model includes two trash cans, designated as Dustbin A and Dustbin B, which will primarily be kept in public spaces. Dustbin B cannot be used until Dustbin A is completely full, however Dustbin A may be utilised. Once Dustbin A is full, Dustbin B can only be utilised since Dustbin A won’t open until the garbage in Dustbin A is removed. Every time a trash can is full, a communication is sent to the appropriate authority. This will prevent the trash can from overflowing. Depending on whether an obstruction is present, trash cans have an automatic close and open feature. Our system uses an ultrasonic sensor to measure the quantity of trash in the trash cans, IR sensors to detect the existence of obstacles, and a GSM system to send information to the authorised control room..

Impacts of climate change on groundwater quality in Coimbatore smart city areas of Tamil Nadu, India

Impacts of climate change on groundwater quality in Coimbatore smart city areas of Tamil Nadu, India

Influence of Urban Green Spaces on Quality of Life and Health with Smart City Design

Publicly available green spaces are great places for people to relax. Currently, the deficiency of such spaces is decreasing daily, especially in urban regions. Urban green spaces (UGSs) have become a topic of great importance in enhancing life expectancy and health. To overcome these issues, the current research highlights the importance of UGSs for the residents’ living quality and urban health. UGSs are relevant for analyzing and investigating better urban lifestyles and development. To perform the experimental work, a green laboratory (GL) in a smart city (SC) area was involved in the investigation. The GL was made of wood, and different types of green infrastructure were analyzed. The research investigation resulted in upgrading the locality. Semi-structured interviews were conducted to enhance the quality of the research. Interviews with residents, occupants of offices, and government experts were conducted. Special survey questions, i.e., quantitative and qualitative, were developed while considering the current demands of the residents. A total of 500 responses were recorded, and by using the MAXQDA software, an analysis was carried out. The results showed that there was a dire requirement for UGSs in terms of size and quantity because of security and opportunities. The proposed research results will provide an opportunity for open spaces to be created in this local district. To fully improve residents’ living style and health, the necessity of deploying UGSs became more apparent. Finally, it became clear that green spaces are necessary to improve the country’s economy.

AHSS—Construction Material Used in Smart Cities

With the level of development of the smart city, there are more and more research sub-areas in which the latest material and technological solutions are used, enabling the proper management and functioning of these cities. On the one hand, the introduced materials and technologies are designed to facilitate the functioning of residents both in the urban space and at home; on the other hand, the implemented solutions strive to be consistent with the principles of sustainable development. As shown in this article, reports on new technical and technological solutions and their positive and negative effects are strongly emphasized in publications on the development of smart cities. The most highlighted materials research in the smart city area concerns smart materials and their characteristics and applications. A research gap in this area is in the presentation of material solutions, particularly materials intended for the load-bearing structures of vehicles (electric vehicles, flying vehicles) or infrastructure elements (buildings, shelters, etc.) designed to increase the durability of the structure while reducing its weight. This paper aims to comprehensively present the most important research areas related to the functioning of smart cities in light of previous research, with particular emphasis on new material solutions used for thin-walled load-bearing structures in smart cities made of AHSS (advanced high-strength steel). These solutions are very essential for smart cities because their use allows for the installation of additional devices, sensors, transmitters, antennas, etc., without increasing the total weight of the structure; they reduce the number of raw materials used for production (lighter and durable thin structures), ensure lower energy consumption (e.g., lighter vehicles), and also increase the passive safety of systems or increase their lifting capacity (e.g., the possibility of transporting more people using transports at the same time; the possibility of designing and arranging, e.g., green gardens on buildings; etc.). AHSS-welded joints are usually characterized by too-low strength in the base material or a tendency to crack. Thus, the research problem is producing a light and durable AHSS structure using welding processes. The research presented in this article concerns the possibility of producing welded joints using the Metal Active Gas (MAG) process. The test methods include the assessment of the quality of joints, such as through visual examination (VT); according to the requirements of PN-EN ISO 17638; magnetic particle testing (MT); according to PN-EN ISO 17638; and the assessment of the selected mechanical properties, such as tensile strength tests, bending tests, and fatigue strength checks. These methods enable the selection of the correct joints, without welding defects. The results have a practical implication; advanced production technology for obtaining AHSS joints can be used in the construction of the load-bearing elements of mobile vehicles or parts of point infrastructure (shelters, bus stops). The obtained joint is characterized by adequate strength for the production of the assumed structures. The originality of the manuscript is the presentation of a new, cheaper, and uncomplicated solution for obtaining an AHSS joint with good mechanical properties. The application of the presented solution also contributes to sustainable development (lower fuel and material consumption use by mobile vehicles) and may contribute to increasing the load capacity of mobile vehicles (the possibility of transporting more people).

Face Mask Detection in Smart Cities Using Deep and Transfer Learning: Lessons Learned from the COVID-19 Pandemic

After different consecutive waves, the pandemic phase of Coronavirus disease 2019 does not look to be ending soon for most countries across the world. To slow the spread of the COVID-19 virus, several measures have been adopted since the start of the outbreak, including wearing face masks and maintaining social distancing. Ensuring safety in public areas of smart cities requires modern technologies, such as deep learning and deep transfer learning, and computer vision for automatic face mask detection and accurate control of whether people wear masks correctly. This paper reviews the progress in face mask detection research, emphasizing deep learning and deep transfer learning techniques. Existing face mask detection datasets are first described and discussed before presenting recent advances to all the related processing stages using a well-defined taxonomy, the nature of object detectors and Convolutional Neural Network architectures employed and their complexity, and the different deep learning techniques that have been applied so far. Moving on, benchmarking results are summarized, and discussions regarding the limitations of datasets and methodologies are provided. Last but not least, future research directions are discussed in detail.

Initiation, marketing and branding of smart city projects: a study of decision processes

ABSTRACT Today, smart city areas and initiatives are found throughout the world, yet little research has been completed into the processes whereby decisions concerning the initiation, marketing, and branding of smart city projects have been taken. The present study examined these processes via interviews with 18 smart city managers, followed by an online World Café which was convened to discuss emerging issues. Interviewees were asked to relate stories of how decisions had been reached, which stakeholders had been prioritised, the extent of citizen co-creation in project initiation and branding, and the main difficulties involved. An argumentative narrative discourse methodology was employed to analyse the interview transcripts, which revealed a number of disparities between the suggestions of extant place branding literature and current practice where smart city projects were concerned.

Optimized RNN-based performance prediction of IoT and WSN-oriented smart city application using improved honey badger algorithm

Internet of Things (IoT) has been widely utilized as the major significant element of Information and Communications Technology (ICT) for feasible smart cities due to the capability of IoT for supporting sustainability in numerous domains. There is a need for fault avoidance via the continuous and dynamic utilization of network behavior for achieving the necessary quality of the IoT communication system that allows us to get sustainable enhancement in smart cities regarding IoT communication systems. While considering the IoT-assisted network, the basic part of the IoT model is considered a Wireless Sensor Network (WSN), especially for data management that consists of various sensor nodes in the smart city area. Moreover, every node in a WSN is considerably utilized for a specific reason and thus, every node is handled by a battery that increases the consumption of energy in the entire smart city scheme for processing the data regarding communication. On the other hand, there exist various limitations like scalability, communication latency, centralization, privacy, security, etc. Thus, this paper plans to develop the IoT and WSN-based smart city application using novel intelligent techniques, aiming for the optimal performance classification of the network. The infrastructure of IoT will consist of WSN, Vehicular Ad-hoc NETwork (VANET), Mobile Ad-hoc NETworks (MANET), Radio Frequency Identification (RFID), and Wireless Body Area Networks (WBAN). Here, the efficiency of the whole IoT system is acquired from the efficiency of the whole IoT module. Hence, the IoT network efficiency rates of the individual must be predicted in an earlier stage to predict the effectiveness of the complete IoT system. The efficiency of each network is forecasted with the help of the constraints such as energy consumption, gathered data size, transmitted data size, mobility, false positive, throughput, packet loss, and delay. The output from each network is considered as input to the Optimized Recurrent Neural Network (ORNN) for predicting the ending superiority of the whole IoT network. Here, the parameter tuning in the RNN is done by the Self Adaptive Honey Badger Algorithm (SA-HBA). The empirical outcomes confirmed that the designed method has forecasted and enhanced the superiority of a whole simulated IoT system in an accurate manner. Throughout the result analysis, the given designed method attains minimum energy consumption rate and also better prediction accuracy.

Waste Management with the Use of Heuristic Algorithms and Internet of Things Technology.

Studies have been performed to improve the process of waste management. They were fulfilled by changing the base of waste logistics management using a combination of intelligent algorithms and the IMPACT IoT platform instead of a human factor. The research was carried out on the example of real data with respect to waste management in a given area. The proposed solution includes a program that simulates the filling of specific waste containers located in various areas. The determined aspects are inconveniences on the routes, affecting the time of moving between the receiving points and the distances between the containers. The variability of the speed and intensity of the containers filling up over time is an additional factor taken into account. The proposed methods yielded the performance of the control of the containers' filling status in real time, which apparently results in the possibility of a reaction to the current demand just in time. The proposed solution enables the improvement of the waste logistics management process, including avoiding the too-frequent emptying of containers or overfilling them. The combination of the device prototype, the simulation program, and the developed algorithms opens the possibility for further research in the smart city and optimization areas.

Development and Application of Smart SPIN Model: Measuring the Spectrum, Penetration, Impact and Network of Smart City Industries in South Korea

The research agenda on smart cities has increasingly extended not only on perspectives of social–economic relations between technologies and cities but also on the industrial economic ecosystem. The purpose of this study is to focus on an analytical method for the characteristics of a smart city’s ecology and industry. With that thought, we have developed a smart SPIN (Spectrum, Penetration, Impact and Network) model and applied it to analyze the ecology of the Korean smart city industry in general. This model consists of smart spectrum model, smart penetration model, smart impact path model and smart network clustering model. The smart SPIN model shows great potential as an analytical method for the smart city industry ecosystem. As a source of data for analyses from 1960, 1985 and 2015 via input–output table, we revised these data into 25 and 8 industries related to the smart city ecosystem. Additionally, we applied the 2015 GDP deflator. The results of analysis are as follows: First, spectrum, the number of smart industries is increasing. This means that the smart city industry scope and area are expanding. Second, analysis of the smart penetration model and smart ecological industry can be applied into other industries. In other words, traditional industries can crossover and utilize smart technology. Third, with the results of our analysis of the smart impact path model, production paths are increasing while parameter paths did not show a triple parameter path. This means the value chain of the smart city industry is highly divested, but the structure of the industry is weakening. Fourth, smart network analysis shows important clusters to be centered on traditional industries: the clusters do not appear in smart industry centers. This means the impact of the smart city is not strong. Our analysis shows that, today, the Korean industrial ecosystem of smart cities is interacting with existing industries and raising it to a more intelligent and smarter level. Thus, there is a need for this kind of analysis study in order to find optimized smart city industry ecosystem.

Bibliometric Mapping of Trends, Applications and Challenges of Artificial Intelligence in Smart Cities

INTRODUCTION: The continued growth of urbanization presents new challenges. This, in turn, will lead to pressure for sustainable environment initiatives, with demands for more and better infrastructure in the diminishing space available and improved quality of life for city dwellers at a more affordable cost. Smart Cities are part of the solution to the growing challenges of urbanization. The adoption of new technologies like artificial intelligence (AI) is transforming cities, making them smarter, faster, and predicting opportunities for improvement.
 OBJECTIVES: This study is conducting a detailed bibliometric survey to investigate the applications and trends of Artificial Intelligence research for different areas of smart cities and emphasizing the potential effects and challenges of AI adaptation in smart cities over the past 30.5 years.
 METHODS: For this study, the Scopus database was used to collect a total of 1925 documents published between 1991-2021 (July). The bibliometric analysis includes document types, subject categorization, document growth, as well as top contributing sources, countries, authors, and funding sponsors. It also analyses keywords, abstracts, titles, and characteristics of most cited documents.
 RESULTS: The analyzed findings of this research study reflect not only the significance of AI technology for various applications within numerous sectors in the smart city but also major obstacles in AI research for various sectors of smart cities.
 CONCLUSION: The research demonstrates that AI has the ability to construct today’s and tomorrow’s smart cities, but that each region’s potentials, conditions, and circumstances must be addressed in order to achieve a smooth internet city development.

Edge AI and Blockchain for Smart Sustainable Cities: Promise and Potential

Modern cities worldwide are undergoing radical changes to foster a clean, sustainable and secure environment, install smart infrastructures, deliver intelligent services to residents, and facilitate access for vulnerable groups. The adoption of new technologies is at the heart of implementing many initiatives to address critical concerns in urban mobility, healthcare, water management, clean energy production and consumption, energy saving, housing, safety, and accessibility. Given the advancements in sensing and communication technologies over the past few decades, exploring the adoption of recent and innovative technologies is critical to addressing these concerns and making cities more innovative, sustainable, and safer. This article provides a broad understanding of the current urban challenges faced by smart cities. It highlights two new technological advances, edge artificial intelligence (edge AI) and Blockchain, and analyzes their transformative potential to make our cities smarter. In addition, it explores the multiple uses of edge AI and Blockchain technologies in the fields of smart mobility and smart energy and reviews relevant research efforts in these two critical areas of modern smart cities. It highlights the various algorithms to handle vehicle detection, counting, speed identification to address the problem of traffic congestion and the different use-cases of Blockchain in terms of trustworthy communications and trading between vehicles and smart energy trading. This review paper is expected to serve as a guideline for future research on adopting edge AI and Blockchain in other smart city domains.

Transmission Line Planning Based on Artificial Intelligence in Smart Cities

With the development of smart cities, it is particularly important to realize scientific and reasonable planning of transmission lines as the backbone of the power transmission system. Through the geographic information system (GIS) platform, this paper obtains the geographic information of the planning area. Then, through the typical design cost of the 110 kV transmission line subvolume of the typical cost of the power transmission and transformation project of the State Grid Corporation and the local documents of the smart city planning area, this paper obtains the estimated cost of each grid after gridding in the smart city area. After that, the research uses the ant colony algorithm to search for the optimal transmission line route in the smart city. Finally, the achievements of primary economic and technical indexes are evaluated in transmission line planning of smart city.

Open Data Based Machine Learning Applications in Smart Cities: A Systematic Literature Review

Machine learning (ML) has already gained the attention of the researchers involved in smart city (SC) initiatives, along with other advanced technologies such as IoT, big data, cloud computing, or analytics. In this context, researchers also realized that data can help in making the SC happen but also, the open data movement has encouraged more research works using machine learning. Based on this line of reasoning, the aim of this paper is to conduct a systematic literature review to investigate open data-based machine learning applications in the six different areas of smart cities. The results of this research reveal that: (a) machine learning applications using open data came out in all the SC areas and specific ML techniques are discovered for each area, with deep learning and supervised learning being the first choices. (b) Open data platforms represent the most frequently used source of data. (c) The challenges associated with open data utilization vary from quality of data, to frequency of data collection, to consistency of data, and data format. Overall, the data synopsis as well as the in-depth analysis may be a valuable support and inspiration for the future smart city projects.