Keywords

1 Introduction

While there is a plethora of practitioner literature on the concept of a smart city, there is a dearth of academic work on the subject. Indeed, as it relates specifically to the area of Fourth Industrial Revolution (4IR) technologies that city planners generally tap into to assist them with designing their smart cities, very little theoretical or empirical academic work exists on the subject. Furthermore, despite the large body of work on these technologies and how they can assist city planners in designing their smart cities, there is no single article that pulls all these technologies into a document so that policymakers can peruse, compare, and contrast ideas as they seek the most appropriate technology for their smart city. This chapter aims to fill that gap in the academic literature by providing a single document that outlines all the possible 4IR technologies that city planners can access to build their smart city. The chapter will become a major reference point for policymakers interested in designing smart cities in their country.

Indeed, the technologies highlighted below will go a far way in assisting city planners in using the vast amount of data to make informed decisions on the future of their cities. For instance, policymakers will be able to tap into technologies such as the Internet of Things (IoT) to stimulate the use of advanced sensors and wireless communication in all kinds of physical objects. Critically, the use of sensor technologies will be able to create substantial volumes of data, thus providing a fine-grained digital view of the physical world. With these data now in hand, smart city planners can now use smart systems that optimize the use of infrastructure and resources in a more informed way (Ward et al., 2015).

To achieve the research objective as stated above, the remainder of the chapter is organized as follows: the next section will provide a brief background to the concept of smart cities and show some of the major challenges of designing such a city. The section will also provide a definition of what is meant by a smart city so that readers can be aware of how this new development differs from just having a city as an urban construct. Subsequently, the chapter will provide a list of the 4IR technologies that are heavily used to drive and facilitate the concept of a smart city. It will, among other things, show some of the issues ranging from the connection of citizens to commerce, access, and use of information communications technologies (ICT), information sharing, upgrading of transportation systems and other infrastructure, etc., that these technologies have used to make a smart city possible. The chapter will end with some concluding remarks and point to a direction for how city planners can incorporate these 4IR technologies into their planning process to facilitate the Smart Cities of the Future.

2 Smart Cities and the New Technologies

Geoffery West, a renowned physicist, is a household name in the work on smart cities. He predicts that the planet will be dominated by cities over the next couple of years. This is because urbanization has been expanding at an alarming rate over the last 200 years, according to West. Urbanization also comes with significant problems. These include but are not limited to environmental damage due to high levels of pollution, health problems, diseases, financial problems to keep budgets within limits, energy crises to keep moving, transportation systems, factories, households, etc. Finding a smart way to overcome these problems is exactly at the heart of the concept behind smart cities as more of the world is moving toward urbanization.

The data on urbanization put into context the great need for cities to become smarter for the future. Indeed, West (2011) quoted some very sobering statistics on the subject. He noted that every week for the foreseeable future, by 2050, more than one million people will be added to cities. Furthermore, one of the largest populations on earth, China, is expected to build 300 new cities in the next two decades. The United States, which a few centuries ago had very few urban areas, is now 82% urbanized.

With this mass urbanization and with the future growth of the world population, which is predicted to reach the 10 billion mark by the end of this century, and more persons wanting to live in cities, the problem of planning and effectively managing cities will become much greater and more sophisticated. The use of technologies will enable planners to better plan and design effective strategies to address mass urbanization, which comes with significant problems. The 4IR technologies will provide a strong enabler to help city planners better address the management of the various issues in their cities. Technology will be at the heart of smart cities.

2.1 What Are Smart Cities?

The most cogent definition of the concept of a smart city is espoused by Microsoft, one of the world’s leaders in technological advancement. It noted that a “smart city is an urban area that uses an array of digital technologies to enrich residents’ lives, improve infrastructure, modernize government services, enhance accessibility, drive sustainability, and accelerate economic development.” This definition encapsulates the need for digital twenty-first century technologies as the backbone of the cities of the future. These technologies will allow city planners and managers to gain a fulsome view of their city’s operations, infrastructure, and necessary service delivery demanded by their citizens.

Indeed, as Microsoft noted, digital technologies can help city planners design solutions to the following:

  • Protect and connect with residents and businesses.

  • Improve accessibility for all people in the community.

  • Support businesses and fuel economic growth.

  • Share information with the public.

  • Streamline government operations.

  • Deliver user-friendly community services.

  • Provide reliable, intelligent infrastructure.

  • Drive environmental sustainability.

  • Promote cross-agency collaboration.

  • Upgrade public transportation.

  • Manage city resources to avoid waste.

  • Collect and analyze data to obtain valuable insights.

There is no doubt that as the urban population continues to grow, citizens will demand more significant levels of service and want those to be delivered on time, with greater levels of efficiency and at a cost-effective fee as well. City managers and planners will therefore require sophisticated technologies that will assist them in planning and overseeing the operations of their city so that they can deliver on the benefits of city life for residents and businesses alike.

2.2 Benefits of Smart Cities

The practitioner literature is replete with examples of how citizens and businesses can benefit from smart cities and generally from urban centers. West (2011) noted that cities are generally vacuum cleaners that suck up creative people, generate cutting-edge ideas, and drive wealth creation and economic growth. These benefits normally drive people toward cities compared to those who remain in rural areas. With the increase and improvements in digital technologies, urban centers have become much more smart and, as such, can provide innovative services and solutions to overcome the general problems associated with urbanization.

With the use of digital technologies, smart cities normally deliver:

  • Improved quality of life for citizens and businesses alike through shorter commutes to work, safer streets, green spaces, and increased economic opportunities.

  • Better services such as modern utilities, intelligent infrastructure such as transportation, banking services, healthcare, etc. The technology is helping cities to better streamline their transportation system to have a more modern multimodal logistics operation.

  • Stronger economic growth because businesses are typically drawn to these cities for the creative talent of citizens, better communication systems, reliable infrastructure, and more sophisticated consumers. Indeed, Porter (1990), in his diamond model of competitiveness, spoke to the need for sophisticated buyers and sellers as strong enablers for the competitiveness of an economy. Cities are known to be vital enablers of economic competitiveness precisely because they have a larger pool of more sophisticated customers and suppliers who demand more from their businesses and force them to innovate and grow (Williams & Morgan, 2013).

2.3 Innovate or Die

Deloitte (2022) predicts that over 55% of the world’s population now lives in urban areas, and by 2050, this percentage will increase to over 68%. With this massive growth in urbanization in such a short space of time, if cities do not innovate, they will definitely face the strong possibility of collapse as the demands of citizens and businesses become increasingly stronger and more sophisticated.

To start the innovation journey, cities must first have a clear vision for their future and a clear road map to implement the same. Without a starting vision, innovation will not be possible, as there will not be an environment to facilitate creativity and resources directed to support the innovation agenda. With a clear vision and the right leadership, cities can start the innovation journey to deliver higher quality of life, economic value creation, and long-term sustainability. This leadership entails a collection of personnel with the appropriate skill set, the emotional intelligence to motivate the people to reach a higher level of creativity, and the necessary supporting technologies. These features, according to Deloitte, are critical characteristics of a smart city leader (Deloitte, 2022).

The smart city will deliver a quality of life that enhances every aspect of its citizens’ existence, including but not limited to safer streets, green spaces, and efficient means of commute, among other things. Indeed, what makes the city smart compared to other urban living is that the smart city provides the best of urban living while minimizing the hassle of city living. A part of smartness is the need for businesses to be creative and generate new economic value, create high-value-added jobs, and drive an innovative economy. In addition, being conscious of the environment and sustainably using natural resources is a crucial characteristic of the smart city concept.

To drive the growth and innovation needs in smart cities, data will be critical. Smart cities will need to have data to properly plan and design strategies to overcome the general problems that come with urbanization. Given the quantity and quality of data in urban centers, to capture the information and use it to generate creative solutions and deliver a high quality of life, economic innovation, and sustainable consumption of resources, the support of technologies will be very important. This chapter focuses on critical 4IR technologies that can be used to facilitate the development of the Smart Cities of the Future. These technologies are important because the cities of the future will be led by smart automation powered by ICTs as opposed to over 200 years ago when the steam engine was the driver of the Industrial Revolution process. The next section of this chapter brings together a suite of 4IR technologies that can be used to facilitate and support the drive toward smart cities.

3 4IR Technologies for Smart Cities

The history of the modern industrialization agenda can be traced back to 1782, with the steam engine as the major technology to drive industrialization of cities and countries. Engineering science was critical to designing the technology to drive power generation and mechanical automation. Fast forward to 131 years after the steam engine technology, which powered the Industrial Revolution, the Second Industrial Revolution was powered by the conveyor belt, the newest technology to drive the automation process. This is a period in human history where mobility was a key driver of the Industrial Revolution; thus, the conveyor belt became an important technology to move items from one place to another in a more efficient way. Within four decades of this new development in the industrialization process, human thinking evolved, and more technologically efficient solutions were being designed to drive the Industrial Revolution. By 1954, electronic automation led by computers became the driving force in the Third Industrial Revolution. Just a mere 172 years after the steam engine, the technological efficiency of the Industrial Revolution process has improved tremendously, with electronics being the driving force behind the new phase of the Industrial Revolution.

Nevertheless, as humans’ innovative and creative skills have advanced, newer technologies and smarter ways of working have become the norm. A mere six decades after the electronics revolution, the Fourth Industrial Revolution arrived with cyber and physical systems driving smart automation, which is the current phase of the Industrial Revolution. Indeed, with smart automation coming after 200 years of steam engine technology, this current wave of the Industrial Revolution will need advanced and sophisticated technological solutions to drive innovation at the country and city levels. This wave will deliver a higher quality of life, economic value added, and a sustainable future.

The rapid advancement in science and technology over the last 200 years has led to the development of a number of sophisticated technological breakthroughs, which can assist city planners in further advancing the quality of life of their citizens and businesses and taking the hassle out of urban living. This chapter provides a comprehensive but not exhaustive list of these new technologies, which are part of the 4IR drivers that can facilitate the movement of urban centers to smarter cities.

3.1 The Technologies

As the Fourth Industrial Revolution unfolds, smart cities are leveraging the pace and scope of ground-breaking scientific and technological advances to better assist in their planning and designing strategies to meet the demands of citizens and businesses. These technologies include but are not limited to artificial intelligence and machine learning, big data analytics, cloud computing, the Internet of Things (IoT), robotics, cobots, and intelligent automation. These emerging 4IR disruptive technologies would enable smart cities of the future to rapidly adapt to change and provide a flexible structure and operational approach that facilitates interaction with a wide range of stakeholders, including alignment with industry, government, and global citizens.

3.1.1 Big Data

Big Data are defined as having volume (e-commerce, mobility, and social media that generate large amounts of data), velocity (generating new data at a rapid pace), and variety (data in many different formats: emails, documents, images, videos, etc.) (Kitchin, 2014). This 4IR emerging technology is the fuel that would operationalize the efficiency and effectiveness of smart cities of the future. According to du Sautoy (2019), 1 exabyte (1018 bytes) of data is created on the internet every day, roughly the amount of data that can be stored on 250 million DVDs. To add, humankind now produces in 2 days the same amount of data that was generated from the dawn of civilization until 2003. The plummeting prices of computer processing power will continue to fuel the prominence of big data intelligence on a scale unimaginable just a few years ago for the future design and operation of cities.

For architects and urban planners, collecting and analyzing data to inform design decision-making have always been a natural stage in the early phase of designing cities. However, until now, this early stage of the design process called programming has been limited to a manual process. Grounded in research and decision-making, programming is a solution-seeking and problem-solving process in which city planners seek to understand the design problem they are trying to solve. To solve the complex design problems of smart cities, urban planners employ this human-centered programming process to interview hundreds of potential users to gain a deeper personal understanding of their experiences to inform the design solution. This process also includes research on hundreds of city design precedents, building and zoning codes, building materials, pedestrian and vehicular patterns, energy consumption, etc.

The rise of big data intelligence can now reduce the collection and analysis from months to weeks. Urban planners can leverage their firm’s Big Data Intelligence cloud infrastructure to ingest the above structured and unstructured disparate data sets. They can employ machine learning (ML) and artificial intelligence (AI) to gain deeper insights by extracting themes, patterns, and trends from the data. This might not be humanly possible. Furthermore, algorithms can learn from past precedent performances and make predictions about what 4IR emerging technologies would achieve operational excellence in the design and human-centered experiences of smart cities of the future.

As observed earlier, big data is the 4IR technology that fuels the efficiency and effectiveness of smart cities of the future. If we continue to witness 1.3 million people moving into cities every week (West, 2011), Smart Cities of the Future will need big data analytics to keep pace with the massive amounts of data being collected by sensors created by the IoT and shared from disparate mobile devices. For example, transportation professionals would be able to quickly access more up-to-date and comprehensive data for every road in cities every day of the year. Entire cities would become a transportation data set full of unexploited potential. City planners and engineers would be able to use computer algorithms and ML to gain deep insights into data to generate answers to questions they did not even know they could ask (Streetlight, 2022).

Big Data Deep-Insight Analytics dashboards powered by AI that analyze data from sensors and IoT devices for pattern recognition would enable city dwellers and operators to gain real-time urban informatics for answering questions such as:

  • What will create congestion in Cities of the Future? (Al Nuaimi et al., 2015)

  • Where would congestion occur a month from today?

  • How long would the congestion last?

  • Which alternative routes would I be able to take to reach my destination without losing time?

  • What would be the impact of traffic flow on connecting residents to key city centers during the labor day weekend?

  • For this year’s Tour de St. Johns, which city routes would separate cyclists from cars and pedestrians?

3.1.2 Cloud Computing

If big data is the fuel that would operationalize the efficiency and effectiveness of smart cities of the future, cloud computing is the container that holds the fuel. Cloud computing’s cost-effectiveness, scalability, elasticity, reliability, security, and global availability make this 4IR technology essential for storing, processing, and mining the huge amounts of big data that cities of the future would generate (Cryptopas, 2020). To engage with their citizens more effectively and actively, governments of future smart cities would be able to rent computing resources from Amazon, Microsoft, or Google to leverage intelligent data generated from disparate sources to improve the performance of health, transportation, energy, education, and water services, leading to higher levels of comfort for their citizens (Mohamed et al., 2015). In recent years, businesses seeking to gain a competitive edge have been quick to embrace this model where the cloud provider is responsible for the physical computing hardware and for keeping it up to date. These cloud computing services include infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) (Microsoft, 2022).

In the words of Marc Andreessen (2011), “Software Is Eating the World.” This Software-as-a-Service 4IR cloud computing service is scaffolding the critical infrastructure for Smart Cities of the Future shaping digital marketplaces in connecting citizens to commerce and services—the Digital Platform Economy (Microsoft, 2022). The most impactful companies of the past decade have been software platforms: Airbnb; Alibaba; Alphabet (Google) Amazon; Apple; and many more that do not start with the letter “A”. According to McFadyen (2021), these software platform businesses have transformed entire industries: Amazon vs. retail; Airbnb vs. hotels; Apple vs. record companies; Uber vs. taxis; Instacart vs. grocers; DoorDash vs. restaurants; Craigslist vs. newspaper classifieds, etc. According to McKinsey, more than 30% of global economic activity—some $60 trillion— could be mediated by the digital platform economy in 6 years (McKinsey Global Institute, 2017).

To add, a 2018 Accenture study of the readiness index for Government as a Platform (GaaP) indicated that three in four citizens globally say government needs to tackle complex issues by collaborating with citizens, companies, and nongovernmental organizations (NGOs). Furthermore, 60% of citizens globally would themselves take an active role in personalizing government services, and seven in ten start-ups/entrepreneurs globally find that collaboration with public agencies is key to their companies’ innovation activities (Le Masson, 2018). The term “Government as a Platform” is used to refer to the whole ecosystem of shared application programming interfaces (APIs) and components, open standards, and canonical data sets, as well as the services built on top of them and governance processes that keep the wider smart city system safe and accountable (Pope, 2019).

In the Smart Cities of The Future digital platform economy, the government as a platform acts as an intermediary to facilitate collaboration, connect citizens to commerce providers, and coordinate to deliver next-generation public services. This can be done through the orchestration of the IoT cloud services that receive, transmit, and monitor information signals from interconnected nodes (sensors) throughout cities. For example, in Spain, ICT company Telefonica has installed sensors that are attached to refuse containers to report, in real-time, how full they are—which means refuse collectors do not have to waste time traveling to bins that are only half full. It also means that key performance indicators (KPIs) can be more closely tied to bottom-line impacts, such as how many bins are close to overflowing and will not be emptied within the next few hours (McKinsey Global Institute, 2018). However, sensors alone are not sufficient. Smart Cities of the Future would need a mature software IoT platform to manage the sensors, receive and process data, and make these data available to smart solutions through application program interfaces (Dubbeldeman & Ward, 2020). According to Kirwan and Zhiyong (2020), the Software-as-a-Service (SaaS) 4IR cloud computing service is scaffolding the critical infrastructure for Smart Cities of the Future shaping digital marketplaces in connecting citizens to commerce and services—the Digital Platform Economy.

3.1.3 Internet of Things (IoT)

The Internet of Things refers to the massive use of advanced sensors and wireless communication in all kinds of physical objects. The wide-scale use of sensor technology creates massive volumes of data providing a fine-grained digital view of the physical world. These data can be used by smart systems that optimize the use of infrastructure and resources (Ward et al., 2015). To add, pervasive computing in Smart Cities of the Future would entail a vision of the world in which computing is not limited to tablets, smartphones, and laptops. The realization of this vision, called the “Internet of Things,” is the ever-expanding collection of connected devices that capture and share data (Ornes, 2016). As city governments begin to unlock the full potential of urban data platforms, AI, smart devices, and interconnectivity, the need for IoT will grow exponentially, leading to efficient problem solving, smart mobility, sustainability, and more (Appleton, 2021). For example, public transport routes can be adjusted in real time according to demand, and intelligent traffic light systems can be used to improve congestion (Marr, 2020). In smart cities, each building can be outfitted with applied intelligence smart-energy meters with human-like capabilities that mimic cognitive functions—learning from volumes of data to increase the efficiency and effectiveness of the electric grid.

These applied pervasive intelligence agents include swaths of tiny sensors that will track everything in the city, from steps and calories to humidity and light (Scientific American, 2014). In addition, with a projection of 27.1 billion connected IoT devices in 2025, former Google and Alphabet executive chairman Eric Schmidt said it best when he made this bold IoT prediction: “[T]he Internet will disappear. There will be so many IP addresses, devices, sensors, things that you are wearing, and things that you are interacting with that you will not even sense. It will be part of our presence all the time” (Thomas, 2022). In sum, the IoT enables more efficient use of resources, improvements to services and safety, and creates a greater sense of connectedness within emerging smart cities (Butler & Lachow, 2016).

As we reimagine Smart Cities of the Future, it must be borne in mind that, currently, the most important generator of city data is a familiar tool: the ubiquitous mobile phone. These devices are, in effect, personal sensing devices that are becoming more powerful and more sophisticated with each product iteration (Pentland, 2015). Each mobile phone personal sensing device leaves breadcrumbs of who you called; who called you; where you are; how you move; how much you spent and where you spent; who you are with; who else is around; your health data; browsing, email, and apps history. This kind of data capture is critical for planning in smart cities, and highly complex and sophisticated technologies will need to be deployed to help city planners make sense of these data.

3.1.4 Artificial Intelligence (AI) and Machine Learning (ML)

We live in a technology marvel where computers continue to speed up while the price of processing power continues to drop precipitously, doubling and redoubling the capacity of machines. This is driving the advance of ML—the ability of computers to learn from data—and the push for AI (Aoun, 2017). In addition, AI technologies can perceive, learn, and reason to extend the capabilities of people and organizations, making them a pivotal 4IR technology enabler for smart cities of the future. As such, AI and ML 4IR technologies would be employed to extract patterns from live and historical data to diagnose and predict what measurable actions city officials should take to improve data-informed decision-making. Let us take energy systems as an example. It will be observed that in a system where energy spikes tend to occur, AI and ML can learn where they usually occur and under which circumstances, and this information can be used for better management of the smart power grid (Choudhary, 2019).

Furthermore, smart cities of the future could employ AI to optimize city services such as garbage collection, vehicle and pedestrian traffic, electricity use, and parking space based on myriad algorithms. However, “being smart” is more than just technology; it is about creating liveable, equitable, and sustainable cities where 4IR technology is first and foremost an enabler to support solutions for addressing urban challenges such as depletion of resources (financial and environmental), inequality, and climate change (Comer, 2016).

Similarly, in securing smart cities of the future, an intelligent network of sensors can capture hackers’ behavior and patterns of attacks, while ML could use the large metadata generated from the sensors to create training data to be used to predict when the right indicator will be deployed to protect the cyber-physical infrastructure before a cyberattack happens (Charles, 2016). Sending the right indicators to protect the right machines before a cyberattack would be equivalent to healthcare professionals predicting what part of your body would be attacked by a disease and dispatching a protective medication to that specific area of the body before the disease attack occurs. The volume of patient data and scientific knowledge has increased to a level that cannot be understood or handled by humans anymore without the help of technology. As such, AI and cognitive computing will be applied to assist health professionals in interpreting medical data to establish the right diagnosis and define the most effective treatment. In addition, the increasing data volume combined with new 4IR technologies such as big data analytics, AI, and ML would create opportunities for better risk assessment to assist financial service providers who are highly dependent on their ability to estimate risks (Dubbeldeman & Ward, 2020). The ultimate goal is for AI to assist in the self-regulation of cities of the future as living systems. If we think of city governance as the process of triage, then self-regulating smart cities would use AI and ML to monitor systems in real time and anticipate problems.

3.1.5 Robots, Co-bots, and Intelligent Automation

Robotics, intelligent automation, and drones are some of the fastest-growing 4IR technologies. When coupled with IoT, these would be the vanguards in reimagining how we design, manage, live, work, and engage with each other—harmoniously with machines—in sustainable smart cities of the future. Furthermore, the McKinsey Global Institute (MGI) confirmed that AI can be combined with complementary technologies such as robotics to provide integrated solutions, including autonomous driving, robotic surgery, and household robots that respond to stimuli (Woetzel et al., 2018). A major 4IR innovation of relevance for Smart Cities of the Future is robots acquiring cognitive and social abilities. They use AI and speech recognition to interact with people through natural language. They also recognize and respond to human emotions and express their own emotions (Dubbeldeman & Ward, 2020). For example, robots now analyze stocks, write in def and informative pros, and interact with customers (Gray, 2016). In China, cobots—machines that can work in factories safely alongside human beings—are upending that country’s vaunted manufacturing sector, allowing fewer laborers to be vastly more productive (Aoun, 2017). Indeed, according to the market research firm, Mordor Intelligence, algorithmic trading accounted for approximately 60–73% of the overall United States equity trading in 2020. This is a critical area for the future of smart cities (Mordor Intelligence, 2022).

4IR Cognitive Robotic Process Automation (RPA) tools and solutions leverage AI technologies such as Optical Character Recognition (OCR), Text Analytics, and ML to improve the experience of the workforce and customers. For example, predictive analytics can enable a robot to make judgment calls based on the situation that presents itself, while ML can enable the system to learn, expand capabilities, and continually improve on its own (NICE, 2022). Intelligent Automation is the next logical step Robotic Process Automation (RPA) is growing toward. Ideal for automating complex systems for smart cities of the future, intelligent automation is an advanced form of RPA that combines technologies such as structured data interaction (SDI), RPA, ML, natural language processing (NLP), natural language generation (NLG), AI decision systems, chatbots, and more (10×DS, 2020).

4 Securing the City’s Critical Infrastructure

Securing the city’s critical infrastructure from manmade and natural catastrophic threats would require deliberate planning to mitigate disruption in services. In addition, planners must consider that every intelligent node depends on complex, interconnected cyber systems—if not fortified—that can be the weak link through which the adversary can attack the city’s critical infrastructure systems. A city’s critical infrastructure sectors can include the chemical sector; commercial facilities sector; communication sector; critical manufacturing sector; dams sector; defense industrial base sector; emergency services sector; energy sector; financial services sector; food and agriculture sector; government facilities sector; healthcare and public health sector; information technology sector; nuclear reactors, materials, and waste sector; transportation systems sector; and water and wastewater systems sector (Ustun, 2021). It is clear that cyberattacks on any, some, or all of these critical infrastructure sectors can have direct impacts on things such as life-sustaining medical devices, industrial control systems running a power grid, a smart sensor indicating the malfunction of a plane’s engine, or tools that examine water contamination. When planning future cities, it is more important than ever to bridge cybersecurity and operational risks to effectively protect critical infrastructure and business operations (LogRhythm, 2022).

Cyber-physical systems (CPS) are at the center of the unification of what have always been distinct physical and virtual worlds. While the convergence of our physical and virtual worlds is not conceptually new, it is the capability that CPS possess that creates one of the greatest intellectual and technical challenges of our time (Trevino, 2019). For example, a cyber incident or attack affecting the systems that control nuclear facilities or dams could be devastating if it resulted in the flooding of a city downstream from a dam or an explosion that spreads radiation over a wide radius (McCarthy et al., 2009).

Overall, while the 4IR technologies are critical to shaping and facilitating the city of the future, a fundamental issue that must be borne in mind is the security and safety of the technologies. Any breach or attack on these technologies will pose a huge risk to the efficient operations of these cities. Therefore, before employing these technologies, policymakers must perform the necessary risk analyses to assess which technology will give the best outcome.

5 Conclusion and Ways Forward

This chapter provides a comprehensive but not exhaustive list of Fourth Industrial Revolution technologies that are crucial to driving the operationalization of smart cities in the future. As urbanization increases and more of the population starts living in urban centers, the demand on city planners becomes more onerous as citizens and businesses require fast and efficient services, higher quality of life, and greater economic value-added and a more sustainable future. Put simply, citizens will want the benefits of urban living with less hassle of normal city life. The smart city aims to generate hassle-free living while giving citizens and businesses the benefits of city life. To effectively achieve this goal, planners will need sophisticated and complex planning tools to assist them in making the best decisions on all aspects of city life from efficiency in transportation to the consumption of natural resources in the most sustainable way.

Planning will, therefore, require a vast amount of data to generate critical information to aid in the decision-making process. To adequately capture these data, process it, and make sense of the information, the Fourth Industrial Revolution technologies itemized and explained in this chapter provide a strong portfolio of tools that planners can access to assist them in making better and more robust decisions in the execution of their smart city. Aggregating these technologies into one place where policymakers can compare and contrast their benefits and drawbacks is a strong value-added, which this chapter brings to the extant literature that focuses on technologies that can drive smart cities of the future. The technologies highlighted above will go a long way in assisting city planners in using the significant amount of data gathered through Internet of Things technologies to make informed decisions on the future of their cities. Data that will drive the development of smart cities, however, given the volume that is to be generated, human capacity will not be able to process the same. It will require algorithms powered by these 4IR technologies to process and make sense of the large volume of data to assist city policy-makers in decision making. The insights from this chapter will be useful to help in the selection of the most appropriate technologies for this purpose.