Emerging Trends, Issues, and Challenges in Big Data and Its Implementation toward Future Smart Cities

Systems thinking for developing sustainable complex smart cities based on self-regulated agent systems and fog computing

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.

Dubai is a smart city: this cannot be contested. The city has labelled itself as a globally recognized successful smart city and it has set in place a vision and a strategy to achieve the goal to become a smart city and to keep this status. Therefore, to sustain its competiveness, the Government of Dubai is considering the massive, fast and diverse data moving quickly everywhere creating what is known as “Big Data” era. This data is becoming the most important source of valuable insights and ultimately helping to make more informed decisions. Despite the growing demand and hopes with the big data, legal and ethical issues related to accessing data remains the main challenge. Therefore, in 2017, Dubai has announced its new Big Data Regulations Act aiming at regulating the big data usage and access to improve policies for better quality of life. This comes as part of the Smart Dubai roadmap to prepare Dubai to embrace the future and emerge as a world-leading city by 2021. The new regulations aim at ensuring privacy, security and governance of the data. The paper will explore the new regulatory act, and evaluate how it sustains and develop comprehensive infrastructure for the big data era in Dubai to maintain the city’s vision. Keywords: Big Data, Smart City, Dubai Data Law, Governance DOI: 10.7176/JLPG/95-03 Publication date: March 31 st 2020

With rampant urbanization and industrialization, the quest to become a Smart City is in vogue. Elaborate designs, ideas, and solutions to existing problems are being devised. However, in this race, city planners often neglect the most critical factor related to one’s existence on the Earth, i.e., Sustainability. Designing smart and sustainable cities is a challenge whose solutions are not easy. Also, developing a proposed smart city is a time-consuming process as it involves its foundations, analyzing the needs, latest technology, infrastructure, and topography. This paper aims to analyze the patterns followed by cities worldwide in the quest to make smart cities. This shall also show how newer cities can become innovative based on the work already done by the existing cities through the concept of Inheritance. In order to do this, a dataset comprising 102 cities is analyzed based on six metrics. A combination of the Principal Component Analysis and K-means Clustering technique is used to assist with the analysis of this unlabeled dataset. It is thereby shown that these 102 cities can be identified as belonging to 4 clusters and the cluster properties can then be inherited by any new city poised to become a future smart city.

South Korea has a long history of the planning, development, and management of smart cities to integrate emerging technological advances into complex physical infrastructure. This article explores lessons learned from smart city programs in South Korea to better understand the challenges and opportunities of future sustainable smart city innovation and development. This article conducted a comprehensive review and analysis of South Korea's smart city programs and conceptualized a sustainable smart city framework that will assist policymakers, planners, citizens, and other key stakeholders. This research proposed Governance, Policy, and Services (GPS) as the three pillars of a successful smart city framework, in addition to integrating physical and cyber infrastructures. This article argues that a smart city should function as a service platform that incubates and delivers long-term services to citizens and society. This article also emphasizes that a strong groundwork of the GPS framework will lead to the successful adaptation of innovative technologies and ideas for future smart city programs.

<p>Future smart cities promise to dramatically improve the quality of life and have been attracting the attention of many researchers in recent years. The integration of IoT with their corresponding service delivery models to manage a city's asset securely remains a significant challenge. The deployment of diverse IoT technologies and several architectural components and novel entities of emerging ICT solutions opens up new security threats and vulnerabilities. Large-scale, seamless communication among multiple IoT technologies is highly dependent on the operations of the underlying wireless access technologies such as WSNs, SDR, CR and RFID. We present thematic layered taxonomies to highlight the potential security vulnerabilities, attacks, and challenges of key IoT enabling technologies which underpin the development of smart cities. We also identify potential requirements and key enablers that play a vital role in the development of secure smart cities. Finally, we discuss various open issues that need to be addressed to unlock the full potential of 5G for future smart cities.</p>

In this developing paradigm, heterogeneous network infrastructure is combined with ubiquitous devices for sensing, smart control systems and big data analytics to create “smart cities.” Enhancing the overall quality of life is one of their main goals and they do so through smart services they offer in a broad range of areas such as transportation, healthcare, entertainment (including virtual reality), the environment (including pollution) and energy. To be able to offer those services, the job of big data and their analysis is complicated, since it allows for the extraction of useful insights from the enormous amounts of data that the smart cities produce. The current state-of-the-art research efforts aimed at big data analytics in a smart city setting are investigated and presented in this chapter. In particular, a comprehensive literature review on the big data analytic frameworks for smart cities is provided. Following that, a short talk on IoT and big data is briefed. Owing to different data that the smart cities collect, which frequently have contradictory processing needs, appropriate investigative methods based on the data type are also recommended, depending on the data type. The many smart city applications were investigated and a perspective on the difficulties associated with smart city development was developed. In this chapter, the methods addressing the smart city issues and development are examined, and the possibility for the employment of integrated IoT and big data analytics is presented. Finally, as a case study, a briefing on a call service application for the fire department in a smart city is provided to round up the presentation.

Smart cities are becoming more and more popular. Currently, there is no unified and interoperable system which could be reused and redeployed in future smart cities. Having an interoperable: (1) system, (2) architecture, (3) workflow to process IoT data, (4) interoperable applications and services, and (5) secure access to data is becoming essential to reduce development cost in smart cities and ensure interoperability among vertical IoT applications (i.e., domain-specific). Firstly, we survey existing work integrating semantic web technologies to Internet of Things, also called 'Semantic Web of Things' and applying it to smart cities. Secondly, we share in this paper, our vision of Semantic Web of Things applied to smart cities and highlight main research challenges. Finally, the main contribution of this work is the semantic engine applied to IoT and smart cities. Moreover, the proposed semantic engine is applied to three use cases: Machine-to-Machine Measurement (M3) framework, FIESTA-IOT EU project and VITAL EU project.

Artificial Intelligence (AI) is one of the science fields with huge potential to create a cognitive and tech-leaping type of future smart city design/development. However, extant studies lag behind recent applications, potential growth areas, and the challenges associated with AI implementation. This study examines AI’s current role, trend, and future potential impacts in enhancing smart city drivers. The methodology entails conducting a Systematic Literature Review (SLR) of publications from 2022 onwards. The approach involves qualitative deductive coding methods, descriptive statistical analysis, and thematic analysis. The findings revealed the impacts of AI in (i) public services and connectivity, (ii) improving accessibility and efficiency, (iii) quality healthcare, (iv) education, and (v) public safety. Likewise, strategies, such as collaborative ecosystems, digital infrastructure, capacity building, and clear guidelines and ethical framework, were proposed for fostering the integration of AI in potential future smart cities. This research fills a notable gap in the current understanding of AI’s specific contributions to smart cities, offering insights for stakeholders in urban planning, computer science, sociology, economics, environmental science, and smart city initiatives. It serves as a strategic guideline and scholarly research output for enhancing smart city design. It also underscores the potential of AI in creating dynamic, sustainable, and efficient urban environments.

Smart cities have been proposed as information technology strategies to generate solutions for the benefit of large cities to improve their quality of life, through phenomena identification tools that use artificial intelligence. Some work has been aimed at developing the infrastructure for monitoring events and the Internet of things, others merely on data analytics without an application system context. This work cites various investigations on data science processes of the smart cities and reports some of its works whose main topics are planning for the start of a smart city, the framework for the analysis of smart cities, and smart cities big data algorithms for sensors location. In these cases, the experiences in these cases are described as well as the trend towards a new process with the form of monitoring-analysis-evaluation-found pattern-driving object-decision-making and the future of smart cities is finally discussed.

In today’s modern society, video surveillance is a growing trend and it can revolutionize many aspects of technology, especially in future smart cities that will transform traditional surveillance systems into intelligent and interconnected networks. It may be difficult for even well-trained employees to process and respond immediately to monitored data. Moreover, IoT-enabled surveillance systems overcome the challenges and flaws of conventional passive monitoring techniques by offering real-time surveillance and automated notifications for suspicious activity, intrusions, or anomalies. Therefore, the objective of this article is to provide an Internet of Things (IoT)-based smart surveillance system that may successfully connect the ecosystem, resulting in enhanced monitoring for smart city services. The primary goal of this study is to provide a comprehensive review of several IoT-based surveillance techniques used in various smart city applications. The categorization of tasks for each section is as follows: to present the historical context overview; to examine the significance of IoT and its application in smart cities; to present a standardized architecture for IoT-based smart city surveillance; to highlight an authoritative and thorough review of current IoT-based smart surveillance systems; and to identify various research issues. The methods used are: statistical graph or chart approach, schematic, and timeline diagram. Conclusions. This article outlines numerous research challenges for future video surveillance that may be addressed by researchers. In summary, this comprehensive review provides a valuable and streamlined resource for future researchers exploring smart city surveillance through the IoT.

Smart solutions shape for sustainable low-carbon future: A review on smart cities and industrial parks in China

The concept of a smart city is still debatable and yet gives attention to every country around the globe to provide their community with a better quality of life. New ideas for the development of a smart city have always evolved to enhance the quality, performance, and interactivity of services. This paper presents a model of a smart city based on the comparison of the chosen smart cities in the world and used the model to validate the requirements for the transformation of an urban district to a smart city. The proposed model for a smart city in this paper focuses on two major components, which are by utilizing IoTs (Internet of Things) in forming a model for a smart city and incorporating culture diversity. The relationship of components and culture influence are the foundation of designing the model of a smart city. In this research, the model of a smart city has been validated based on the requirements analysis from the survey instrument and the results show that the average mean of each element used is more than 4 out of 5. The model of a smart city can be used as a guideline for transformation of an urban district to a smart city.

It is already true that Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. A large number of fields and sectors, ranging from economic and business activities to public administration, from national security to scientific researches in many areas, involve with Big Data problems. This talk is aimed to demonstrate a close-up view about Big Data, including Big Data applications, Big Data opportunities and challenges, as well as the state-of-the-art techniques and technologies that we currently adopt to deal with the Big Data problems. The second part is to discuss the deep learning role in Big Data. In recent years, deep learning caves out a research wave in machine learning. With outstanding performance, more and more applications of deep learning in pattern recognition, image recognition, speech recognition, and video processing have been developed. Restricted Boltzmann machine (RBM) plays an important role in current deep learning techniques, as most of existing deep networks are based on or related to it. This talk will also discuss how the big data relates with the deep learning.

As the world population grows along with increase in urbanization, cities are getting more and more populated and increasing demands on various natural and man-made resources. Making cities smart through the appropriate application of the plethora of innovative new technologies and paradigms would help mollify potential environmental problems/constraints in such cities. Besides their significance in solving environmental problems, smart cities also aim to improve citizen's quality of life and efficiency of public services by optimizing the costs and resources involved. Smart city applications are founded on various enabling technologies and processes related to communication and networking, real-time control and big data analytics, to name a few. These constituents of a smart city infrastructure need to be integrated appropriately and seamlessly for provisioning efficient services to citizens. Each enabling technology has its own unique properties. The interplay and interaction among smart city constituents and their unique properties raise unique security and privacy challenges. In this chapter, we overview enabling and emerging technologies and security and privacy challenges for smart cities. Ensuring authorized accesses to these constituents is critical for ensuring the security of smart cities. We present existing solutions to these challenges mainly from the perspective of access control (AC) with a special focus on risk management, trust, insider threats and secure interoperation. Finally, we present future research directions.