Era of Computational Big Data Analytics and IoT Techniques in Smart City Applications

Internet of Things (IoT) and Big Data have played a significant role in the development and sustainability of Smart Cities. They are the backbones of Smart Cities' efforts to connect human resources, social capital, and ICT infrastructure to address public challenges, achieve sustainable development and improve people's standard of life. It helps Smart Cities improve public services, such as water management, healthcare, education, security issues, transportation, energy usage, and other community to achieve a better life. Big Data helps to analyze, store and back-ups a massive amount of data generated in smart cities in seconds day by day. For this matter, different analytical tools are employed, such as data analytics, machine learning, statistics, and data mining. Even though there are many benefits offered to smart cities; the Smart Cities encounters challenges that need to be addressed. Many of these challenges focus on security and privacy, infrastructures and operational and handling massive data. This paper describes the overview of IoT, Big Data, and Smart Cities. The Applications of IoT and Smart Cities were also discussed; the features of Smart Cities and Big Data; Different challenges of IoT, Big Data, and Smart Cities are described. Also, the proposed research work has presented the relationship between IoT and Big Data to Smart Cities; the role of IoT and Big Data in smart cities was identified; finally, the future directions for IoT and Big Data regarding Smart Cities are discussed.

A smart city is an urban policy innovation that can improve the community's quality of life by promoting environmental, social, and economic sustainability issues. The involvement and participation of civil society in developing smart cities is a major issue in implementing inclusive smart cities. However, gender issues are often forgotten in developing sustainable smart cities. This article examines two issues. First, the importance of gender issues integration in the development of sustainable smart cities in Indonesia. Second, the importance of gender mainstreaming policy in the development of smart cities in Indonesia. This is a desk study or literature study. Data were obtained from research results published in national and international journals. Data was obtained through accredited journal search engines, namely google scholar, SagePub and Researchgate. The research results show that development of smart city in Indonesia is not yet gender responsive, causing gender inequality gender and excluding women from development. To respond to this, thus there is a need for gender mainstreaming policies in developing smart cities through an overview of the challenges of gender mainstreaming in developing smart cities. Thus, this research recommends a gender mainstreaming strategy as a policy in developing smart cities in Indonesia. Gender mainstreaming policy in smart city development need to be to create a smart city life that is just, inclusive and involves women in development.

The study aims to avoid the phenomenon that thousand cities seem the same in the construction of smart cities and the efforts of all walks of life are jointed to implement the construction of smart cities and the creation of city brands. First, the basic theory of smart city construction is introduced. Second, the restricting and promoting factors influencing smart city construction and development are analyzes, and the evaluation system of smart city development is established. Then, the model for smart city construction and development based on the neural network is implemented. Finally, some domestic cities are selected as the dataset to build a training model, and the city brand optimization strategy is proposed. On this basis, an evaluation system for smart city development based on the intelligent neural network and Grey relational analysis Back Propagation Neural Network (GRA-BPNN) is obtained. The entropy weight method (EWM), grey relational analysis (GRA) method and the evaluation method based on Technique for Order Preference by Similarity to an Ideal Solutionv (TOPSIS) are regarded as the members of the control group, and the results of different methods for evaluating the development of smart cities are compared. The results show that the modeling of smart city construction based on neural networks can help to implement an evaluation model for smart city construction and development, and it can help evaluate smart city construction and development accurately. And then the corresponding strategies are proposed to speed up the construction of smart cities with its local characteristics, and then city brands are built. Compared with other evaluation algorithms, the performance of the algorithm proposed is better and more stable and the evaluation results are more reasonable than those of the others, which can prove that the evaluation algorithm is feasible and scientific. This study provides a new idea for the application of deep learning to smart city construction and city brand building.

Due to the incompleteness of planning ideas and construction methods, there are many problems in urban construction: the planning lacks prospectiveness, does not match the development needs of the city, and repeated construction is common; the community has insufficient functions and transportation. Therefore, it is of great significance to explore the path of smart city construction and development. This article mainly studies the application of intelligent logistics technology and big data in the construction and development of smart cities. Starting from the two main theories of theory and reality, this article first discusses the challenges of the big data era background to urban construction, analyzes the relationship between big data and smart cities, and then takes urban logistics big data as an object to study smart city construction. The smart logistics technology pointed out the convenience brought by the smart logistics technology and big data technology in the construction of smart cities. Finally, by drawing on the advanced experience of using big data in some cities at home and abroad to promote the construction of smart cities, the use of big data and smart logistics Technology assists the construction of smart cities, and has made concrete and detailed suggestions. The experimental results of this paper show that the group size is 60, the number of iterations is 30, and the minimum logistics cost through iteration is 1,284,100 yuan. In this paper, the logistics management method of intelligent logistics technology based on big data can minimize the logistics cost. This article provides some theoretical guidance for the key technical aspects of logistics network warehousing, service and resource management in the construction and development of smart cities, and provides guarantee for urban construction and stable development, which has certain reference significance for better and longer-term development.

Smart Cities (SCs) have recently opened new lifestyles as they introduce effective approaches for improving urban management. These cities integrate Industry 4.0 technologies and new organizations into a social and technical system. A Smart City (SC) finally aims to integrate urban business, transportation, water, energy, and other subsystems by analyzing the data collected from sensors and Information and Communication Technology (ICT). In this regard, the current article proposes a hybrid structure based on Cloud Computing (CC), cloud processing, and internet technology to develop and manage SCs and urban planning. Moreover, the development and analysis of sensors to construct an SC, as well as supporting technologies, are addressed. Therefore, the present research is focused on defining and reviewing large data and objects of the Internet and CC to identify the current challenges and limitations. This research, thus, introduced a novel approach in the context of the Internet of objects, whose data are gathered from different geographic locations through devices and sensors to be used in a new system. CC services in a city can analyze and make smart decisions to optimally manage SCs and improve the welfare of citizens. This study consequently sets the path for further investigation into the problems and difficulties associated with Big Data (BD) applications in SCs.

Big data and artificial intelligence based early risk warning system of fire hazard for smart cities

Chapter 5 - Blockchain-based energy-efficient smart green city in IoT environments

The concept of smart cities transformed as global implementation is hampered by a host of technical, economic, and government road barriers. In addition, the integration of Internet of Things (IoT) and big data technology has opened new horizons in terms of smart home technology and smart city development that is yet to be explored. IoT is a technology that allows devices to connect to the Internet, and applications are designed to meet the needs of the community. Communities are very interested in using this and other information technology in cities to build smart cities in recent years. It is important to consider big data analytics (BDA) when using IoT in a small ecosystem because there is less data to be managed than a big city where there is data from more smart devices and people BDA aims to make data informed decisions on the basis of raw facts provided. Aside from the fact that there are many articles in the literature that talk about the BDA as a decision-maker in smart cities, general research on BDA and smart cities focuses on the technical or intellectual properties of a particular smart city.

This paper aims to explore the most important disruptive technologies in the development of the smart city. Every smart city is a dynamic and complex system that attracts an increasing number of people in search of the benefits of urbanisation. According to the United Nations, 68% of the world population will be living in cities by 2050. This creates challenges related to limited resources and infrastructure (energy, water, transportation system, etc.). To solve these problems, new and emerging technologies are created. Internet of Things, big data, blockchain, artificial intelligence, data analytics, and machine and cognitive learning are just a few examples. They generate changes in key sectors such as health, energy, transportation, education, public safety, etc. Based on a comprehensive literature review, we identified the main disruptive technologies in smart cities. Applications that integrate these technologies help cities to be smarter and offer better living conditions and easier access to products and services for residents. Disruptive technologies are generally considered key drivers in smart city progress. This paper presents these disruptive technologies, their applications in smart cities, the most important challenges and critics.

Smart Cities are well planned, designed, and established keeping in mind the growing need of citizens in search of better livelihood. Technology has played a big role in equipping Smart Cities to offer better facilities to its citizens in terms of better living comfort, better atmosphere, better surrounding, better medical facilities, and most importantly ease of doing business, office, and day to day activities. While doing so, IT Infrastructure and online transactions have influenced all the operational processes of Smart Cities and almost acting as its backbone. Obviously, any adverse impact on online transactions can create chaos in Smart City operations. To address this concern, a safe and reliable online transaction is a must. In this paper, we have discussed Blockchain Technology-based solutions for Smart Cities and their potential impact on Smart Cities Development. We specifically tried to address the concern of how Smart City online operational processes for various applications can be made reliable and safe by using Blockchain Technology and how this technology can benefit Smart Cities overall development. Based on the comprehensive research and detailed literature review, we proposed Blockchain Technology based secure framework for Smart Cities. We also identified various applications and process areas that can be highly benefited by using Blockchain Technology and can make these applications smarter and more reliable and fit for use for any Smart City.

The rapid development of smart cities has raised concerns about residents' emotional well-being (EWB). To enhance EWB when developing smart cities, policy-makers should take residents' perceptions and attitudes into account. How can residents' perceptions about smart city development help promote their EWB? In this paper, we constructed a comprehensive model to explore the effect mechanism of perceived smart city developments on residents' EWB by considering the factors of stress, convenience, and life satisfaction (LS). Using a sample of 428 urban residents in a Chinese smart city, the paper verified the conceptual model by using a structural equation model (SEM) analysis. The results showed that: (1) perceived smart public service (PSPS) can increase EWB by reducing stress; it can also increase EWB by the mechanism of improved LS, brought about by this reduced stress. Perceived smart infrastructure (PSI) will reduce EWB by increasing stress; it can also decrease EWB by the mechanism of reduced LS, brought about by increased stress. (2) Perceived smart public administration (PSPA), PSPS, PSI, and perceived smart environmental protection (PSEP) can enhance EWB via the mechanism of increasing convenience and thereby improving LS. (3) Finally, the statistically insignificant relationship between convenience and LS may be due to the interaction effect of stress and convenience, because the interaction term between convenience and stress has a significant effect on LS, resulting in four insignificant indirect effects involving PSPA, PSPS, PSI, PSEP and EWB vis-a-vis convenience. Overall, this paper contributes to cross-disciplinary research on residents' perceptions with respect to smart city development, and provides guidelines for governmental policy-making in the planning of smart cities.

Geospatial technology helps in the creation, management, analysis, and visualization of spatial data. For Smart city management and functional applications; geospatial data and geospatial technology are instrumental. In this paper, geospatial technology and its role have been broadly discussed to assess its significance in smart city development. A smart city concept is considered to transform the quality of life in cities through the digitalization of different infrastructure sectors such as transportation, health, energy, education, and environment. Identifying and obtaining valuable information from large amounts of data that is generated in the growing urban areas. Smart city ideas have been implemented in many countries to seek solutions toward resource scarcities, congestion, and environmental issues. Concepts like open data, interconnected systems, internet of things, artificial intelligence, cloud computing, big data, and geospatial intelligence are innovative technologies that are expected to help in various fields of smart city development and give solutions to a variety of problems that the cities are facing.KeywordsSmart cityInternet of thingsOpen dataArtificial intelligenceGeomatics

Smart city with Chinese characteristics against the background of big data: Idea, action and risk

Over the last decade, the evolution of the Internet of Things (IoT) has resulted in a drastic increase in the development of smart cities, including smart parking and intelligent transportation systems (ITS). Smart cities combine a variety of sensors (such as traffic, parking and weather sensors) deployed within these cities. These sensors are used for various applications, such as transportation, parking and weather forecasting. We propose an approach for the mapping of traffic sensors with route coordinates in order to analyze traffic conditions (e.g., level of congestion) on the roadways. We present an algorithm and provide two illustrative examples that cover all of the possible mapping scenarios. We also evaluate the performance of our proposed approach in terms of sensors' correct detection, missed detection and false detection on the routes. Our work can be used for the development of various smart city applications, such as traffic management and smart parking.

In developing countries especially in African continent, rapid population growth in cities is a major concern. Majority of governments in Africa have made more effort to develop urban areas as compared to the rural ones. Social and economic activities are more concentrated in urban areas. This is a pushing factor for the rapid population growth in cities as many people, especially young generation, tend to migrate from rural to urban. This growth leads to excessive exploitation of natural resources, environmental degradation and increased pressure on social services. Rapid increased population acts as an encouragement to construct smart cities for achieving needs for present and future generations. Tanzania as one of the developing countries in Africa has taken initiatives in establishing smart cities. The aim of this study therefore, is to examine opportunities and challenges in the development of Smart cities in Tanzania with a case study of Mbeya city. In addition, conceptualization about development of smart cities is proposed to prioritize the planning of smart grid among other smart city infrastructure systems. Conclusively, Mbeya city has a full potential of many strengths and opportunities for successful development as a smart city.