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Many smart city applications have been proposed and demonstrated over the years; however, moving to large-scale deployment is still scarce. A contributing factor to this scarcity is the lack of well-established engineering methodologies for large-scale smart city applications. This paper addresses engineering methodologies and tools for large-scale...
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... process is detailed in Table 2. Use case requirements for all architecture levels. As a part of the requirements, the SysML use case diagram model is provided in Figure 5 Functional design Black box functional designs and models for each architecture level. Here, the system level details of one involved microsystem and its microservice are provided in Figure 6 Use case design and models for each architecture level ...
Citations
... This characteristic is a key opportunity for energy conservation and reducing the ROI period. The smart streetlight concept aims to leverage this while improving safety and security and enhancing public infrastructure servicing [9][10]. This paper focuses on the design and deployment of smart streetlights in Selangor Cyber Valley (SCV) leveraging LoRaWAN communication. ...
... Intelligent sensors should be interconnected seamlessly and securely, to enable automated high-level smart applications. Smart interconnection of sensors, actuators, and devices enables the development of solutions required for smart city-and CPS industrial solutions [17]. ...
The technical capabilities of modern Industry 4.0 and Industry 5.0 are vast and growing exponentially daily. The present-day Industrial Internet of Things (IIoT) combines manifold underlying technologies that require real-time interconnection and communication among heterogeneous devices. Smart cities are established with sophisticated designs and control of seamless machine-to-machine (M2M) communication, to optimize resources, costs, performance, and energy distributions. All the sensory devices within a building interact to maintain a sustainable climate for residents and intuitively optimize the energy distribution to optimize energy production. However, this encompasses quite a few challenges for devices that lack a compatible and interoperable design. The conventional solutions are restricted to limited domains or rely on engineers designing and deploying translators for each pair of ontologies. This is a costly process in terms of engineering effort and computational resources. An issue persists that a new device with a different ontology must be integrated into an existing IoT network. We propose a self-learning model that can determine the taxonomy of devices given their ontological meta-data and structural information. The model finds matches between two distinct ontologies using a natural language processing (NLP) approach to learn linguistic contexts. Then, by visualizing the ontological network as a knowledge graph, it is possible to learn the structure of the meta-data and understand the device’s message formulation. Finally, the model can align entities of ontological graphs that are similar in context and structure.Furthermore, the model performs dynamic M2M translation without requiring extra engineering or hardware resources.
... The term "Smart City" today is extremely trendy for everyone involved in city governance, but it is still relatively unclear not well-defined, despite there are a lot of different definitions in the literature. For example, first time this concept was described in 1992 as the development of the city towards technology, innovation and globalization [10]. Kustra and Brodowicz in their article [16] even have created a consolidated table where they have listed main existing descriptions of Smart Cities. ...
If we speak about the Smart City’s transport system, autonomous vehicles idea is the first thing that comes to mind. Today, it is strongly believed that the autonomous vehicles’ introduction into the traffic will increase the road safety. However, driverless cars are not the solution by itself. The road safety and, accordingly, sustainability will strongly depend on decision making algorithms inbuilt into the control module. Therefore, the goal of our research is to design and test the data mining algorithm based on Entity–Attribute–Value (EAV) model for decision making in the Intelligent System in the fully- or semi-autonomous vehicles. In this article, we describe the methodology to create 3 main modules of the designed Intelligent System: (1) an Object detection module; (2) a Data analysis module; (3) a Knowledge database built on decision rules generated with the help of our data mining algorithm. To build the Decision Table on the base of the real data, we have tested our algorithm on a simple collection of photos from a Polish two-lane road. Generated rules provide comparable classification results to the dynamic programming approach for optimization of decision rules relative to length or support. However, our decision making algorithm thanks to excluding the mistakes made on the object detection stage, works faster than existing ones with the same level of correctness.
... Visvizi et al. [21] 2020 Sustainable smart cities and smart villages research: Rethinking security, safety, well-being, and happiness Talari et al. [22] 2017 A review of smart cities based on the IoT concept Delsing et al. [23] 2021 Smart City Solution Engineering ...
... As small and medium-sized enterprises (SMEs) gain more extensive clientele and greater visibility for their product, they may collect and utilize an increasing amount of data. Furthermore, cloud integration enables SMEs to preserve and handle enormous data sets gathered from several sources [21][22][23]. ...
A smart city is an urbanization region that collects data using several digital and physical devices. The information collected from such devices is used efficiently to manage revenues, resources, and assets, etc., while the information obtained from such devices is utilized to boost performance throughout the city. Cloud-based Internet of Things (IoT) applications could help smart cities that contain information gathered from citizens, devices, homes, and other things. This information is processed and analyzed to monitor and manage transportation networks, electric utilities, resources management, water supply systems, waste management, crime detection, security mechanisms, proficiency, digital library, healthcare facilities, and other opportunities. A cloud service provider offers public cloud services that can update the IoT environment, enabling third-party activities to embed IoT data within electronic devices executing on the IoT. In this paper, the author explored cloud-based IoT applications and their roles in smart cities.
... Also, prosperity in various dimensions of society will translate into a change and improvement in the quality of life of city dwellers as well as energy management processes in cities and also in individual households [9]. Cities are therefore becoming organisms that are more complex, elaborate, complex and multi-faceted structures [10][11][12]. More and more often, due to the requirements of cities and their inhabitants, cities will use modern technologies and intelligent solutions in occupations of economic or social sectors [13,14]. ...
... As a result, the idea of a smart city is implemented quite successively at various stages. The concept of a smart city first appeared in 1992, describing the development of the city towards technology, innovation and globalization [12]. Currently, smart cities and smart city communities can be defined as systems of people that interact and use the flows of energy, materials, services and financing to catalyze a sustainable economy, development, resilience and high quality of life [15]. ...
... 10 The profile, applications and smart solutions are provided by free webinars 11 Regular app maintenance gives residents confidence that their actions are in place reliable. 12 Keeping your profiles safe prevents attacks on residents. ...
Personalization, mobility, artificial intelligence, corporate life transferred to the online world-all these elements will shape all intelligent solutions, including those for cities in the future also in the field of energy management. A necessary condition is to determine which specific repetitive behaviors and features smart cities will have to meet in order to build an image among residents and adapt to their preferences and requirements and energy requirements. Smart cities were created to support residents in using various services, to give them the possibility of easy communication without time and local barriers. Therefore, high-quality smart solutions in cities significantly affect trust in the city and can affect its reputation. Given that the purpose of the article is to examine the perception of intelligent solutions also in the field of energy and their impact on the sense of privacy and security, different exchanges of perceptions of quality, the risks they pose to residents and their perception of what gives a picture, have been studied. The results of empirical research clearly showed that the safety and level of satisfaction with the activities carried out by the city have a significant impact on the perceived quality, which in turn has a positive impact on reputation. The authors proposed a methodology based on the Kano model for examining residents' satisfaction in order to investigate undefined desires and identified and confirmed needs and to study the analysis of risk and potential threats. The study was in the form of a proprietary questionnaire that can be used in similar surveys on the satisfaction of residents; 2685 correctly completed questionnaires were analyzed and the results obtained after submission were included in management action plans. The city government has expressed an interest that the measures taken will be reviewed after one to two years.
Interoperability is a central problem in digitization and sos engineering, which concerns the capacity of systems to exchange information and cooperate. The task to dynamically establish interoperability between heterogeneous cps at run-time is a challenging problem. Different aspects of the interoperability problem have been studied in fields such as sos, neural translation, and agent-based systems, but there are no unifying solutions beyond domain-specific standardization efforts. The problem is complicated by the uncertain and variable relations between physical processes and human-centric symbols, which result from, e.g., latent physical degrees of freedom, maintenance, re-configurations, and software updates. Therefore, we surveyed the literature for concepts and methods needed to automatically establish sos with purposeful cps communication, focusing on machine learning and connecting approaches that are not integrated in the present literature. Here, we summarize recent developments relevant to the dynamic interoperability problem, such as representation learning for ontology alignment and inference on heterogeneous linked data; neural networks for transcoding of text and code; concept learning-based reasoning; and emergent communication. We find that there has been a recent interest in deep learning approaches to establishing communication under different assumptions about the environment, language, and nature of the communicating entities. Furthermore, we present examples of architectures and discuss open problems associated with ai-enabled solutions in relation to sos interoperability requirements. Although these developments open new avenues for research, there are still no examples that bridge the concepts necessary to establish dynamic interoperability in complex sos, and realistic testbeds are needed.
Urban governance is without a doubt a very complicated activity. The city doesn't just consist of people and buildings, there are transport and road infrastructure, critical infrastructure, medical facilities, road cover, industrial equipment and many more. Besides, the city council provides a wide range of services to the public. Among them healthcare, welfare, economic and finance supply, labor, real estate management and others. Information management systems and web services are employed for digital management, while various embedded management systems are used for equipment management and surveillance. Being very complex and multilayered system, Smart City Managment solutions offer a platform that encapsulates main services for both public and for technological aspects of urban governance. The results presented in this paper are based on a study of the existing software, hardware and middleware platforms for smart city use case. The main focus is middleware platform as it serves as medium that can connect existing software and hardware solutions. In the global context of Smart city management service system all major components are broken down in the format of microservices (on the level of large enterprise distributed service). Presented Managment software suit model had been broken down into multiple software architecture abstraction layers, from hardware to end-user application. As a result, the three stages smart city service implementation roadmap had been presented. Using the Middleware platform and Web-services models, the Smart City Managment services can be implemented in any given city in porotype stage for future evaluation and full version implementation.
In recent years, numerous people have been moving toward urban life. By 2030, it is estimated that more than 60% of the population will live in urban areas. Further, the connection between different urban systems such as transportation, communication networks, and trade is remarkably more complex than before. These complexities have doubled the significance of smart cities and the rapid adaptation of cities to the latest technologies. The electric vehicle is one of the new components in the current era that its application in cities can be considered an influential innovation for sustainable urban growth and development. On the other hand, with the expansion of electric vehicles in the transportation industry and the need for energy to charge car batteries, the impact of these vehicles on the network cannot be overlooked. This chapter discusses the presence of electric vehicles in smart cities. Using the smart city and the Internet of Things platform, we can collect data on the behavior of electric vehicle owners and, with the Deep learning method, which is one of the methods of machine learning, predict the charge level of electric vehicles in the arrival to the parking, the location of the car, and the period of connection to the parking.
Purpose The purpose of the study is to solve the problem of numerical evaluation of integral indicators of the development of economic systems and the “smart city” system, as well as to develop an appropriate criterion. Design/methodology/approach The research methodology is based on a primary analysis of regulatory documents and current publications on the development of economic systems and the “smart city” system, as well as the methods of mathematical information theory. On the basis of this approach, the basic concepts of the “smart city” concept were considered, and the analysis of specialized literature was carried out. Originality/value The significant differences in the views of various scientists on the concept of “smart city” are revealed. Contradictions of interests among different groups of stakeholders of the “smart city” (citizens, businessmen, scientists, managers, politicians) can significantly reduce the effectiveness of the solutions being developed. Currently, the degree of the development of the structures of the “smart city” is assessed by formal indicators presented in the standards and guidelines. Considering the “smart city” not only as a system but also as a product, it is necessary to study it from the point of view of the interests of its consumers (stakeholders). Consumers can assess the product quality. To assess the quality of a smart city product, it is necessary to develop a numerical criterion showing the satisfaction of stakeholders’ interests. It is shown that the criterion based on the mathematical apparatus of information theory and statistics “entropy” can be applied as an adequate, accurate, and reliable criterion. For this purpose, the relevant literature is considered, affirming the statements that this approach is universal. The developed criterion makes it possible, based on a sociological survey, to compare different stages of the city’s development and determine the presence of trends toward improving the quality of life when building a “smart city”. Some issues of the formation of a “smart city” in the example of Tula, Tula region, and the Russian Federation are considered. Conclusions It has been established that the main drawback is insufficient consideration of the opinion of the citizens, while the “smart city” should be considered as a product, which should be evaluated by the consumers—the citizens. For an objective assessment, an information criterion of the quality of a “smart city” and evaluation of the trends’ development was created.KeywordsEconomic systemsSmart cityStakeholdersTrendsQualityTheory of informationEntropyJEL ClassificationC51C55L60M21M41P12P17
