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Implementing Data-Driven Strategies in Smart Cities: A Roadmap for Urban Transformation
Implementing Data-Driven Strategies in Smart Cities: A Roadmap for Urban Transformation
Implementing Data-Driven Strategies in Smart Cities: A Roadmap for Urban Transformation
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Implementing Data-Driven Strategies in Smart Cities: A Roadmap for Urban Transformation

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Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions – data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management.
  • Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions
  • Provides a step-by-step and applied holistic guide and methodology for immediate application in the reader’s own business agenda
  • Presents cutting edge technology presentation with coverage of innovations such as the Internet of Things, robotics, 5G, edge/fog computing, blockchain, intelligent transport systems, and connected-automated mobility
LanguageEnglish
Release dateSep 18, 2021
ISBN9780128211236
Implementing Data-Driven Strategies in Smart Cities: A Roadmap for Urban Transformation
Author

Didier Grimaldi

Didier Grimaldi, PhD is Associate Professor at the La Salle–Ramon Llull University, Barcelona, Spain. His scholarly interests span novel forms of innovation to develop new or existing businesses by analyzing different models of public-private governance, which offer a more active role to the citizens. Dr. Grimaldi’s research focuses on evaluating the real effect of emerging technologies (big data, Internet of Things, drones, social media, etc.) to promote new services for citizens that improve their quality of life.

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    Implementing Data-Driven Strategies in Smart Cities - Didier Grimaldi

    Chapter 1: From smart city to data-driven city

    Didier Grimaldia; Kristi Shallab; Ignasi Fontanalsc; Carlos Carrasco-Farréd    a Ramon Llull University, La Salle Faculty, Barcelona, Spain

    b Smart City Consultant, Washington, DC, United States

    c Expert in Organizational and Urban Resilience and Director Europe at Rezilio Technologie, Beloeil, Canada

    d Ramon Llull University—ESADE Business School, Barcelona, Spain

    Abstract

    Global urban population exceeded rural population for the first time in history in 2008, and the United Nations forecast that 66% of the world’s population will live in urban areas by 2050. In Latin America, urban growth will be exceptional, and the forecast is even bigger, that is, 83% in 2030. Cities will consequently be the locus of major challenges like air pollution, traffic congestion, water, and waste management. They will also have to offer economic activity and good well-being for these immigrants coming from the rural zones looking for job opportunities. In this chapter, we develop the five major challenges we believe cities will face as corroborated by other authors. These are short-term issues related to the environment, economic competitiveness, and the quality of life offered but also long-term issues covering resilience and sustainability problems. At present, we are living through an overwhelming sanitary and financial crisis linked to the COVID-19 pandemic crisis. This book is not aimed at just discussing and measuring specific effects on the global economy and people health conditions. We have indeed embraced a wider and larger objective of reflection. Nevertheless, we have included in the following paragraphs the start of analysis of its possible effect.

    Keywords

    Smart city; Data-driven city; Quality of life; Social entrepreneur; Urban entrepreneur; Resilient city

    1: Urban challenges

    Global urban population exceeded rural population for the first time in history in 2008 (Crossette, 2010), and the United Nations forecast that 66% of the world’s population will live in urban areas (United Nations Economic Commission for Europe (UNECE), 2014) by 2050. In Latin America, urban growth will be exceptional, and the forecast is even bigger, that is, 83% in 2030. Cities will consequently be the locus of major challenges like air pollution, traffic congestion, water, and waste management (DESA, 2009). They will also have to offer economic activity and good well-being for these immigrants coming from the rural zones looking for job opportunities. In this chapter, we develop the five major challenges we believe cities will face as corroborated by other authors (Assadian & Nejati, 2011). These are short-term issues related to the environment, economic competitiveness, and the quality of life offered but also long-term issues covering resilience and sustainability problems. At present, we are living through an overwhelming sanitary and financial crisis linked to the COVID-19 pandemic crisis. This book is not aimed at just discussing and measuring specific effects on the global economy and people health conditions. We have indeed embraced a wider and larger objective of reflection. Nevertheless, we have included in the following paragraphs the start of analysis of its possible effect.

    1.1: Environment issue

    Madlener and Sunak (2011) states that cities are responsible for around 75% of the overall resource consumption and thus environment problems, even if they occupy no more than 2% of the land (Miller & Hazel, 2007). The recent report of the World Bank (2017) corroborated it, estimating that metropolitan areas account for 70% of CO2 emissions in the world. Cities are affected by global warming and climate change. Rising sea levels are one of the consequences that directly affect urban areas lying less than 10 m above sea level. As far as industrialized countries are concerned, a first estimation predicts 70% of Europe’s largest cities (e.g., Paris, London, Amsterdam) or megacities like Tokyo or New York City will be affected. In emerging countries, Kolkata (formerly Calcutta, India), Shanghai, and Guangzhou (formerly Canton, China) are mentioned. Also, China alone has more than 78 million people living in vulnerable low elevation cities (McGranahan, Balk, & Anderson, 2007).

    It is important to highlight that every year an estimated 8.8 million people worldwide die prematurely of air pollution, giving rise to an average reduction of 2.9 years in average global life expectancy. The climate crisis has further increased the number of premature deaths. Nevertheless, the drastic prevention measures against COVID-19 propagation have also caused a dramatic reduction in road traffic and industrial activity, which may in turn have resulted in significant reductions in CO2 emissions and air pollution. The percentage differs depending on the countries, for example, between 70% and 80% in France or Spain, and up to 20%–30% in the case of China. This change has generated a reflection that another mode of production and consumption should exist that is greener and more responsible toward the planet. Nevertheless, it is too early to be able to measure if the effect will be long term and will decrease the air pollution levels.

    1.2: Economic competitiveness

    Cities usually have had a profound effect on the economic competitiveness of a country, performing better than the national indicator’s average (Assadian & Nejati, 2011). The city of Tokyo is responsible for 40% of Japan’s GDP while holding only 28% of the country’s population. Similarly, Paris covers 30% of France GDP, with only 16% of the French population living there. Even among developing countries, similar examples can be found. The Nigerian capital, Lagos, forms 30% of the country’s output, while only 8% of the country’s population live there. However, the performance of a city cannot be disconnected to the general business situation of the country (Economist Intelligence Unit, 2004). The existence of transparent national business rules and regulations are among one of the most important economical motivations in attracting new investments to a city. They are conditions for the sustainability and competitiveness of the industry and service companies present in the city.

    The financial crisis of 2007–08 also called subprime mortgage crisis was a severe contraction of liquidity in global financial markets. This crisis originated in the United States as a result of the collapse of the US housing market then spread to the rest of the world. The greatest effect of COVID-19 may be the economic downturn that includes job losses, although the evidence from the 2007 crisis was quite mixed, and outcomes may depend on the governmental measures taken to mitigate the recession. However, the current crisis appears to be much more severe and may lead to a total collapse of certain sectors, such as aviation, entertainment, and tourism, and will therefore have much more profound consequences for the urban economy.

    1.3: Quality of life

    Poverty, hunger, and sanitation problems drastically affect the lives of millions of people in the world. The last financial worldwide crisis initiated in, 2010 deteriorated the existing situation by pushing a lot of citizens into poverty (UNECE, 2014). In 2020, the situation was even worse after the COVID-19 sanitary crisis. A strong health system needs a strong economy, which is in real danger today. The quality of life is largely related to the economic conditions of living. Poverty remains one of the challenging and lasting problems in the city and provokes exclusion from society and social systems (World Bank, 2018). It causes also psychological deficiency among the people who feel they have failed to provide the essentials for themselves and their family (Mwenda & Muuka, 2004).

    1.4: Sustainability

    In common use, the bottom line refers to benefits or losses (depending on the company situation), which are usually recorded in a company’s income accounts. Over the last 70 years, environmentalists and social justice lawyers have struggled to achieve a better definition of the bottom line, seeking to introduce a more perfect accounting for the real effect of company business activities on the planet and society; for example, a company has a financial benefit, but its mining operations cause hundreds of deaths and contaminates a nearby lake. What real costs does this company have for society if the government ends up spending its money on public healthcare and cleaning the lake? To remain viable in the future, companies must focus on sustainability and pay attention to the effect of their actions on key three aspects: environmental, civic, and economic. Technologies enable cities to be prepared to these new risks while being eco-responsible and self-sufficient to a certain degree, which entails urban production and a local supply of food. The concept of sustainability in the urban domain has gained strong attraction due to the diffusion effort of the World Commission on Environment and Development (Brundtland, 1987). In early 2007, it became the dominant approach promoted by the United Nations for urban accounting and theorized by recent studies (De Guimarães, Severo, Felix Júnior, Da Costa, & Salmoria, 2020; Macke, Rubim Sarate, & de Atayde Moschen, 2019; Mora, Appio, Foss, Arellano, & Zhang, 2020). Scientist John Elkington (1994) in an exercise on synthesis defines sustainability according to three variables, each one of them beginning with the letter P: People, Profit, and Planet (Fig. 1.1).

    Fig. 1.1

    Fig. 1.1 Triple bottom line.

    Fig. 1.2

    Fig. 1.2 Kelly Jin, Chief Analytics Officer for the City of New York and Director of the Mayor’s Office of Data Analytics.

    1.5: Resilience

    Cities and societies are also vulnerable. Terrorist attacks such as those occurring in 2015 in Paris in a Media office ("Charlie Hedbo) or 2016 in Brussels or Munich and accidents due to technical failure or human error remind us of this, as do natural disasters that are more frequent today associated with climate change. A smart city needs to be resilient" too and be prepared for major breakdowns. City resilience concepts need to be developed not only for the city infrastructure, but also for the whole city as understood as a network of services prepared to better cope with disruptions causing multiple cascade effects that affect the urban environment and

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