5.1.1. Norilsk, the most polluted and polluting city in the world

Stalin decided to build Norilsk in the 1930s, a city he wanted to be “as beautiful as Leningrad”, in the Russian Arctic: 280 days of extreme cold, 130 days of snow-storms and 45 days of the polar night a year. Just like Saint Petersburg under Peter the Great, the city was built by slave labor since Norilsk was a gulag. It aimed to exploit mines of non-ferrous metals in the Great Siberian North. It only became a city in 1953, after the gulag was closed and 500,000 inmates had worked tirelessly in extreme conditions. Soviet authorities attempted to make it into a real city with model infrastructures and high salaries. Today, it is a closed city, with no communication other than by plane, with reserved access, mainly home to temporary workers and housing with just under 200,000 residents. It is the most polluted and polluting city in the world. While the workers are now there of their own free will and well-compensated, it still has a mono-activity.

Yet, its residents are quick to point out that it was close to becoming a real city:

“Take an atlas of Siberia in 1914 and open the page on Taïmyr: you’ll see that the peninsula was full of small black dots – villages. There were anywhere between 150 and 200 at the time. Whereas today, there are three cities in Taïmyr: Norilsk, Doudinka and Oust-Avam. There is a real difference in mentalities between the residents of Norilsk and Doudinka. In Doudinka, people are very attached to their city, but here people only stay for a short while. This is because Doudinka was built on the location of the old village of Doudinskiï, founded over 400 years ago. People have lived there for generations and are attached to the land. Norilsk, however, was founded in 1939 on virgin soil, 12 km away from Norilskiï, which gave it its name”. [LEC 15]

In other words, there was, and there is, a social capital lying in the Russian Arctic, a people with its history and its traditions that are closely protected. Soviet power was able to make nothing where there was once something. In addition, residents taking part in the interview conclude “Russia always needs to be directed manually”. In sum, Norilsk did not develop endogenously.

5.1.2. Singapore, the smart nation

The Singapore experiment is radically opposite. From the very start, Singapore was imagined by its founder, Lee Kwan Yew, as a Smart city, and furthermore as a Smart nation. What was a disadvantage became an advantage. Singapore has become something where in 1965 there was nothing more than a conglomeration of dirty houses. Singapore is today a city at the confluence of a multitude of activities, which very quickly embarked upon a digital revolution thanks to innovating policies. It is the result, on the one hand, of central planning or, better, global thinking, but, on the other hand, of one that constructs an institutional context that allows cities to develop around its residents’ initiatives and lives. It is designed as a life system and not “machines for living in” in the style of Le Corbusier or Stalinist architects.

It is an example of functional integration that today allows complex systems modeling – that medieval art had intuitively understood. Housing, work and transport are designed in such a way that residents do not spend more than 45 minutes every day commuting, while residents of Mexico City will often spend up to four hours every day getting to and from work. Its famous artificial trees serve to collect rain water and solar energy, and provide climate control, CO₂ processing and pleasantness (Figure 5.2).

Two parallel paths, two diverging destinies: What is the take-away?

First, that a city’s intelligence is its ability to grow organically and form a coherent ecosystem, economically and politically, and one that is able to evolve. What should we learn from the history of Singapore, which could be applied to Russia’s archetypal obsolete urban fabric? Here are four main lessons:

Long-term planning relying on a strategic vision. As early as 1965, Singapore’s visionary Prime Minister was imagining the growth of the city into a smart nation, meaning a global vision of the city as a generator of wealth and well-being – “A city in a garden” – driven by a high level of scientific knowledge helping to integrate technological advances. This vision translates to a 50-year plan, updated every five years to include new creations and unresolved problems and the possibilities offered by new technologies.

An efficient government plays an integrative role in urban functions. Singapore is an archetype of a development-oriented state, very interventionist, and a direct kind of interventionism so to speak from the foundation until the mid-2010s. It then gradually became more and more indirect as the economy grew, to define the institutional framework of the private sector’s vitality. A very professional civil service works laterally around great urban functions. System architecture, as a method for project management is now fully mastered and allows digital technologies to be optimally used in projects centered around functional integration (for example, designing a commute to be under 45 minutes every day) and not technique itself, which allows a better articulation between public governance and deployment by public entities that boast failure rates far below the standards of industrialized countries. The BIM standard (building information modeling) is mandatory in construction to help integrate jobs from maintenance to design.

An articulation between the central role of the government and initiative of actors, a city is an archetype of the strategist state: the atmosphere is favorable to pilot and innovative field projects that are quickly integrated into the global system. To face an ageing population, Singapore implemented an alert system activated by the detection of any behavioral anomaly through multiple sensors that can be placed in households and public areas. Parents, but also any voluntary citizen, can sign up to become a natural care provider and intervene whenever an anomaly is detected. Technology, civism and traditional values are therefore integrated. Singapore is not a direct democracy, but a strong state where transgressions are immediately regulated (which, by definition, is the case for a self-regulating system such as a direct democracy), but considered legitimate by its citizens. As the country develops its social capital through education and investing in innovation, the government sees the need to encourage bottom-up dynamics resulting from social and civic initiative and release its grasp by developing multiple forms of decentralized participation.

Just like Norilsk, Singapore is not a natural city: considering its conditions, it should not exist. Its presence is the result of the political will to make it the smartest city in the world. This suggests strategic state leadership and constant investment in innovation. The success of the city stems from the legitimacy of its vision, which is very different from the case of Norilsk, because it is a shared vision in the case of Singapore. Conversely to what is suggested in predominant economic theory, Singapore’s success is not due to the application of neo-liberal doctrines of free-trade and being open to the winds of globalization, but rather due to vision of the role of the state that is both systemic and pragmatic, described by Kishore Mahbubani, the director of the University of Singapore.

“Asian governments have not looked at government as the problem. Instead, many were convinced that it can provide solutions. (…) Another damaging aspect of the Reagan–Thatcher revolution was the fundamentalist belief that “markets know best”(…). The obvious question in the minds of many Asians is: How could ideology have so blinded him to the realities of actual market functioning, which brought the world to the brink of a total meltdown? (…)

In contrast to Greenspan’s ideological views, most Asian policymakers traditionally worked on the pragmatic assumption that, in the real world, it was important to maintain a balance between the “invisible hand” of free markets and the “visible hand” of good governance.(…) . The “light‐touch” regulation advocated by British and American regulators (in part, as a result of ideological assumptions of the Reagan–Thatcher revolution) has clearly failed. (…) Hence, one key struggle that Asian regulators are facing is how to find the right balance.” Finding the right balance in redesigning their financial architecture over the range of complex policy structures and issues mentioned above will be much more difficult for Asian policymakers in the postcrisis environment.

After this crisis, the importance of good, strong governance has come back with a vengeance. (…) In trying to find the right balance in redesigning the new financial architecture, the Asian governments know they must avoid both extremes: the debilitating heavy‐touch nature of Soviet central planning as well as the irresponsible light touch of the Reagan–Thatcher revolution and financial market fundamentalism”. [MAH 10]

From the very start, President Lee Kwan Yew understood the dynamic of increasing returns to finance the development of Singapore, shantytown in 1965. The vision was to build “a garden city” uniting both aesthetics and quality of life for its residents. The state is therefore both an entrepreneur as it invests directly and initiates projects, and an architect in that it sets meta-rules for developing the city, which are, in this case, very constraining in nature due to its limited geography, and also regarding the examples of catastrophic urban development in cities in Southeast Asia. The natural advantage offered by the port attracted foreign capital that was invested in local development. In doing this, the city-state increased its ability to attract big companies and so forth, the issue becoming how to maintain the city’s coherence and the pace of its growth. Singapore dedicated the constitution of its education capital up to three times the amount of foreign direct investment. Accumulating innovations, the city is able to export them, improving its ability for self-financing. Development presents a new challenge at every stage, and while the city is now hailed as a visionary archetype of the globalized city, it does not escape the risks of social and spatial dysfunctionality present in globalized cities. This drift, dangerous if un-governed, is a governmental preoccupation in a culture centered around equilibria between opposing elements and that fears imbalance and disharmony. This is the new challenge for Singapore.

How can Russia learn from these lessons and turn the burden of monotowns into an opportunity for innovation? Russia is a laboratory for innovation with the renovation of “Kroutchevka” and “Brejnevka”, these buildings similar to our great constructions of the 1960s, where the economic return of urban innovations can be very quick considering the energetic “abyss” that are these installations. An asset could be that the Russians think more in terms of “territory” than “city”, which is the interdependence between a city and its outskirts, while we live in the illusion that a city can be green without ever considering that over 50% of its pollution is imported.

If Singapore is a reference as a smart city, it is that it was designed as such from the ground up. It is clear that it is far more difficult to do the same on constructed urban fabric. Christchurch in New Zealand is now joining the adventure, but only because… it was destroyed by an earthquake in 2011! Physically destroyed but maintaining the social capital of a population with strong traditions of civic involvement that is allowing a bottom-up redesign of the city.

Russian monotowns are a land of opportunity not only for investment and innovation, but also, and perhaps most importantly, for designing a way to transition from a dysfunctional urban fabric to a smart city, which is the question that is asked in emerging countries that will be the stage for urban growth over the next 30 years.

As with any complex project, it is important to start off with pilot projects such as R&D support that will help understand the dynamic of the urban fabric in a specific context. These projects will help stimulate the social capabilities that are at the core of the appropriation of an urban dynamic. The Russian federal government still dedicates US$520 million in social subsidies to monotowns that today no longer produce anything. Transforming these expenses into investments and adding foreign investments would make a return to increasing returns possible. Since the return of the State in Russia and the disappearance of the political power of the “seven bankers” (Semibankirschina) of the 1990s, a fabric of small and medium companies is growing. Russia does not yet have the culture of innovation and is low on the Global Innovation Index, but the scientific level there is excellent and we are seeing the appearance of the first technoparks. As for Singapore and China, foreign investment will be an opportunity to transfer technology and knowledge that will feed an endogenous growth, and help the development of “new city sciences”.

The marginal cost of intelligence is in reality very low on an old urban fabric, since the expenses are generally fatal ones in infrastructure refurbishing expenses: performing these operations intelligently does not cost more than performing them unintelligently, but will reduce future costs a lot more! The marginal cost linked to new technologies does not generally exceed 10%, widely compensated by positive returns in the form of savings on energy, transport and the ability for innovation, which become a source of exportation, which is the case for Singapore, which after importing technology for a while, now exports it.

5.2.1. The African city

Africa is home to approximately 1.1 billion residents in 2017, of which 68% do not have access to water, and 80% of the rural population (600 million people) do not have access to electricity. The natural demographic growth in the continent due to high fertility levels with an average of six children per woman makes the African proportion of the world population in the decades to come alarming. The African urban environment is suffering from the consequences of this demographic growth, even though urban growth is mainly a result of migrations from the rural areas into the cities. Drought, environmental degradation, rural poverty and wars continue to force a great number of villagers to leave for the cities in order to search for other economic and social outlooks. Unfortunately, there is little work available, and this reality pushes city-dwellers to unusual initiatives of social self-innovation¹ pushed by a need for survival, curiosity or change.

This is how Nigeria, the Democratic Republic of Congo (DRC) and Ethiopia have begun to emerge as demographic powerhouses. According to the Population Reference Bureau (2015), in 2050, Nigeria will remain the number one African demographic power, ranked as the fourth most populated country in the world, with 400 million people. Congo will be in ninth position with approximately 90 million people, and Ethiopia will boast 165 million people.

Thus, the African continent, burdened by its demographic growth seems to march on like a sleepwalker towards a future of wasted opportunities and potential instability. Western countries are attempting to contain African migrations rather than to solve the underlying causes. This panorama reveals Africa as a continent that is suffocating under its own urgency. In addition, the time to act is running out. African cities are simply disoriented. They are overwhelmed by the speed at which these changes are occurring and have no control over them. Problems plaguing African cities do not simply stem from a lack of resources and services, but also stem from the severity of Africa’s social disturbances, to high crime rates, levels of corruption and the inefficiency of local authorities. This all has repercussions on water services, electricity, schools and housing.

Smart city projects in Africa must therefore be global development projects that deal with the stability of the city as a sustainable ecosystem, creating economic opportunities, and the development of social capital. Africa has two options when it comes to smart cities: the one adopted by the Senegalese government that has launched a smart city project entitled Diamniado Lake City that has the ambition to rival the likes of New York, Beijing and Dubai². “Nothing will be too big or too beautiful” states the Senegalese government that is granting the construction of the city to foreign investors for the sum of two billion dollars. A project that reeks of Richard Florida’s “creative classes”, except that this one intends to leave behind more than 70% of the population: the Senegalese people that work on the construction site have no access to water or electricity. This island of super rich amidst the poor will have its own business center, international airport, luxury apartments, renewable energies, etc., all while being financed by Chinese investors with no consideration towards the technological independence of the country.

The other option is that of endogenous development, which will integrate high-end technologies by absorption from the populations, from indigenous knowledge systems. To the Diamniado approach that begins from the top down without accounting for populations or territorial capital, are opposed bottom-up approaches that start from the reality of peoples’ lives, in order to link it to high-end technologies through an endogenous and frugal process of innovation.

5.2.2. The emergence of a territorial project through meaning: the case of Rhamna, in Morocco

Moroccan researcher and consultant Amine Belemlih has implemented a novel approach, whereby he accompanied the emergence of a territorial collective project with sense-making dynamics, an example of a bottom-up design of a smart territory. In conjunction with the authorities of this small rural province on the Casablanca–Marrakech axis, Amine asked himself about the creation and development of economic and social fields, not in terms of a result of a national policy, but as the support for a regional project driven by its people, in other words, designing smart territorial specializations that would be driven by organic growth and catalyzed by territorial actors, NGO’s local to agricultural cooperatives, private operators and local collectives.

The challenge is sizeable: how does public decision, which necessarily comes from the top, meet organic dynamics that necessarily come from the bottom? (Figure 5.4). This organic dynamic, when looked at closely, translates to individuals deciding to engage in a common action because it makes sense for them. At the same time, faced with the ambiguity of situations and diverging interpretations that people can make of them, there is no such thing as a plunge into reality through action, which is known as enactment³, to assist this collective sense to emerge, refine and specify itself: this is one of the key concepts of social psychologist Karl Weick on sensemaking, led over the past four decades [WEI 95]. Enactment consists of attempting to transform one’s environment to understand it, which goes hand in hand with the famous quote by Kurt Lewin: “If you truly want to understand something, try to change it”.

In the case of Rhamna, the question is to understand how a territorial network of actors around solidarity sectors can emerge. The objective is to identify the mechanisms, processes and patterns at work that allow such an emergence, with the aim to produce a model of this process that could be useful to other territorial emergences, by integrating contextual variables and specific objectives that can vary. We are in the perspective of a “metamodel” rather than a cooking recipe made of a protocol and purely predictive mechanisms. But what do we mean here by emergence?

“Emergence is the creation of order, the formation of new properties and structures in complex systems. When emergence happens, something new and unexpected arises, with outcomes that cannot be predicted even from knowing everything about the parts of the system”. [LIC 14]

This phenomenon, observed in physical and natural systems is also implemented at the organizational level, the level of collaborative communities and, moreover, the level of social systems. Numerous studies have been performed on these emergence phenomena, in particular the one on the city of Branson [CHI 04] as a major cluster of theater and music-hall performances, on regional clusters or industrial alliances such as the alliance in semi-conductors in the USA in the 1990s, to face the Asian markets [BRO 95]. These studies, to quote only a few, highlight a certain number of determinants and major characteristics of social emergences, in particular:

• – the innovative character of the emergent system (not limited to the sum of the characteristics of individual components);
• – the non-reducibility (to only the components of the system);
• – the reciprocal causality (emergent properties have a bottom-up, top-down and lateral influence on the components of the system and the latter have an influence on the overall system);
• – the increased capacity of the system resulting from this emergence dynamic (the same goes for the amplifying effect of the immaterial capital that develops within a cluster of innovation, for example).

What specifically interests us here is that at the core of social emergence is a continuous current of interactions linking a large number of individuals. Each interaction is activated by organizational forms already in place. The result is a current of involuntary or unintentional emergent structures that appear to restrict behaviors while giving meaning to human action. The same goes for local initiatives around solidary actions, which end up being reinforced by other spontaneous actions to the point of influencing the installation of secondary care centers, etc., giving an aspect of destination or specialization to a particular neighborhood.

A solidary sector is composed of activities that generate revenue developed in the dynamic of a virtuous ecosystem in the context of specific economic sectors, responding to the criteria of the Economie Sociale et Solidaire (solidarity and social economy), in particular the importance of the social bond, of cooperation, transparency, equality between people involved in exchanges, all along the economic value chain. This echoes a similar concept of “short solidary economic circuits” that favor social bonds, cooperation, transparency and equality between people involved in exchanges.

There can be an intentionality of actions at the beginning, impacting local institutional leaders or simple citizens and the entrepreneurial energy invested in this action, which imbalances the established order of things, stimulating their evolution. These actions end up being self-sustaining, driving the social system, at the scale of a neighborhood or a territory, in a new stable state, even though it is always “far from the equilibrium”.

These dynamics of social and organizational emergence go through various phases.

First of all, the social ecosystem evolves towards a state of imbalance: in the case of Rhamna in Morocco, an alarming observation made by the community was that “we cannot go on this way” and that the endemic poverty of local populations, combined with failed local initiatives to develop alternative cultures, called for new ways of doing things that would break the mold. Then comes a phase of launching experimental energy-based actions that literally come and put stress on the system and engage fluctuations in an established order until reaching a threshold: this is the activism of NGOs, cooperatives and local economic operators instigating RGA (Revenue Generating Activities) and incubating new solidary sectors, with a heavy institutional support from the Governor. It is in this context that begins a “Rhamna hive”, a social, provincial, entrepreneurial incubation space, and also the launch of pilot projects of solidarity sectors in chicken and alpine goat farming (yes, indeed, in Morocco) with a strong social dynamic of sensitization of women led by local associations.

The next phase, still currently emerging at the time of writing (2018), is that of nonlinearity, where the positive feedback loops amplify fluctuations, leading to the progressive advent of a new order. For example, in this case, this amplification has taken the form of growing interest from institutions such as the Agence Française de Développement, the World Bank, the Moroccan Ministry of Agriculture and the heads of various neighboring communities to take part in this provincial transformation project, articulated around pilot projects and an integrative and systemic procedure that is implemented as time goes on. One amplification leading to another, Moroccan business owners (CGEM), through their Observatoire des Branches Professionnelles et des Régions (Observatory of Professional Branches and Regions), even offered to make this province a pilot territory in matters of smart territorial specializations, moving towards the emergence of an actual pole of excellence in social and solidary economy.

The third phase is recombining the existing elements (resources, expertise, partners, tools or methods, for example) as a means of increasing, through the acts of synergy and positive side effects, the potentialities of the social collective in emergence. This harkens to the works on autopoiesis by Varela [VAR 79]. In this case, the different action programs unite with others’ projects: bridges appear continuously between initiatives to give birth to meso-initiatives that are constantly being improved and generating increasing momentum from local operators and institutional partners. In Rhamna, this gave birth to pilot projects of new solidary sectors or even new Moroccan regions, such as the region of Smara in the South of Morocco or Marrakech, interested in engaging in similar initiatives with their own stakeholders.

The fourth and final phase of this process is an emergent equilibrium that crystallizes certain institutional or organizational routines. This guarantees that the flow of resources injected into the system is uninterrupted: Rhamna’s history is still being written.

The intention of the ongoing research project is to detect how collective mechanisms of meaning occur during the different phases of emergence, in order to identify the potential patterns allowing us to understand how involved parties make sense of their actions and how these actions lead to experimenting, organizing adapting, etc., the emergent social system in a recursive fashion. This experimental approach aims to enrich existing leadership models by placing them in a tradition of collective construction [LIC 09].

The contribution of the efforts by Amine Belemlih, a research-action project led with the support of the Université Paris-Dauphine, aims to produce a model for the process of emergent meaning in action within the emergence of a social territory. A contribution that is still unfolding, capital for any smart city developer.

5.2.3. Casablanca as a prototype for remedying to the tentacular growth of cities

Casablanca extends over 300 hectares per year. This is the manifestation of the law expressed by West and Bettencourt⁴, the oil-slick extension of a city if nothing is done to prevent it. It is a polluted city, and we can only approximate its number of residents due to the considerable rural exodus and the amount of informal housing. The urbanization model in Morocco generally occurs by “playing catchup”: take into account the inflation in population, proliferation of informal housing, shantytowns that are constantly being urbanized. The process is endless.

Driven by Electrical Engineering Professor Aawatif Hayar, at the University of Hassan II, who directs the research center GreenTIC, the Casablanca smart city project was made a reference project for Africa by the IEEE institute to design a reference model for Africa in order to remedy the situation. Supported by State authorities in the region and the city, the Casablanca smart city project piloted by Aawatif Hayar adopts an approach based on organic growth.

Her premise is the following considerations. In emerging countries, the concept of smart cities is even more pertinent than in developed countries under the double constraint of a high demographic growth and limited resources. The low cost or frugal approach to smart cities that she is offering involves using Information and Communication Technologies (ICT) to effectively use the limited resources of the city and the country. The idea is to represent another alternative for these cities in emerging countries in order to benefit from solutions offered by the concept of the smart city and its inherent dynamic for wealth creation and resource optimization without having to wait to have a large budget available. The basic idea is to create a virtuous cycle starting with people’s needs and optimizing available means to better respond to expectations, opening new perspectives and creating wealth that generates more wealth via proximity.

This new model of the smart city is essentially centered around its people as primary operators of a sustainable and equitable development. It uses digital tools combining the advantages of being both mobile and ubiquitous, which Aawatif Hayar sums up using the neologism mobiquitous, to offer services that are useful to citizens and collect data that is then processed and analyzed to offer other more appropriate services in the aim of a sustainable and equitable global social prosperity.

Emerging nations are faced with the same challenges as developed countries, insecurity, pollution, criminality, transport, housing, education, health, access to water and generally to what Amartya Sen calls capacities, that is, the real capacity to implement multiple “rights of” and “rights to” promoted by international organizations, but in a far more intense manner and with fewer resources, notably digital ones, with African countries being far less connected.

Morocco was able to get into the digital race in time. It is a country where the central power – the King – is very enterprising, in a top-own philosophy, which presents problems with relations with the territory in a country that has almost no middle class and where inequality is high, in particular in terms of education between the ruling class and the people. Thus, in 2013, the king launched the Casablanca smart city project.

The workgroup led by Prof. Hayar used a bottom-up approach to balance the State’s top-down one. Inspired by experiments in developed countries and keeping in mind the limited means and infrastructures of emerging countries, she proposed to limit investment costs by using existing infrastructures, in particular mobiquitous ones such as smartphones and other mobile terminals for developing apps, services and pilot sites and thus creating the building blocks of a smart city, which would then be reinforced by other realizations until creating an interconnected environment. The need for connectivity guaranteeing the development of a positive digital experience is indispensable to help keep the citizens of the future involved and allow them to appropriate the data and services available to develop other innovations and other added value services.

This model, named Ville Intelligente Sociale et Frugale (smart, social and frugal city), has the following characteristics:

• – adopting a participative and equitable e-governance continuously assessed according to performance indicators defined by a global strategy and vision of a smart city;
• – encouraging social innovation to better respond to the needs of citizens;
• – encouraging all actors of society (citizens, researchers, small to medium businesses, start-ups, etc.) to develop services and pilot experiences for smart cities;
• – improve the well-being of residents and their involvement in the development of their city;
• – minimizing costs of deployment and maintenance of a smart city by adopting economic mechanisms and models that favor its sustainability;
• – developing sustainable approaches for extracting;
• – encouraging innovation through the model of “open data for economic development” [OEC 15];
• – transforming the city into a living experimental laboratory on the principle of the living labs that help develop local abilities and enrich R&D and innovation with terrain-based experience and data;
• – adopting an evolving digital transformation of society and economics;
• – using mobiquitous objects and networks (omnipresent and mobile) to develop services to residents based on digital technology;
• – adopting incentivizing economic models based on crowdsourcing and crowdfunding.

These initiatives are integrated into a living labs⁵-type platform. It currently drives a number of projects surrounding Casablanca, in the housing sector, creating revenue-generating activities, in particular the objective of sustaining this project culture with the appropriation of certain technologies around development objectives.

This first family of projects aims to create a living social fabric in the city, beyond the magma created by the appearance of shanty towns due to informal housing. This is to help the city, in the long run, to develop a self-regulating characteristic, to understand its dynamic in order to define evolution diagrams that block oil-slick development and remedy the plagues of cities.

However, the other aspect of the Casablanca smart city program is remedying the exodus from the country to the city. One problem that can occur with the development of smart cities is the risk of excluding city outskirts from development, which will only reinforce rural exoduses. To do this, the e-douar project was launched. It consists of developing a transition zone between a smart city and its environment, to promote human development and create revenue-generating activity, because residents do not leave the countryside because cities are attractive, but because rural life is unattractive. By combining digital technology, alternative energies and ecological construction, the hypothesis is to develop revenue-generating activities, employment, and, at the same time, increase the attractiveness of these areas by developing tourism. The development of basic infrastructures and basic digital services could not only encourage the sustainability of rural housing, but also attract “rurban” residents and organize a “soft transition” between city and country.

The e-douar project is a research-action project that brings together residents in the douar and the University Hassan II. Digital technology is a resource for development and not a deus ex machina, which will inherently provide well-being by itself. The project will test the impact of implanting digital in a rural territory, through an approach based on the appropriation of these technologies by the people to create the uses that they deem pertinent for their development. The idea is therefore to organize a fusion between the realm of digital and indigenous knowledge systems. Here, digital is a base – represented by the smart house that concentrates all activities made possible thanks to digital technology – that allows the development of projects such as a biogas project that uses methane production from organic waste to produce energy for domestic and agricultural activities, while producing quality fertilizer. Digital technology will also help map agricultural lands to develop precision farming, thus reducing the use of fertilizer, optimizing water and cultures.

5.2.4. Angola, Namibia: eco-design of a drinking water supply

Dr Morris Zombo Mussema is an agricultural engineer and Angolan academic. He is heavily involved in the development of municipal communities in response to the shortage in water, a subject that was at the center of his thesis [ZOM 17a]. His action-research consisted of developing a water supply based on indigenous knowledge (similarly to the “révolutions tranquilles” (calm revolutions) described by Bénédicte Manier), and also basing it on a reproducible scientific model.

Beyond Information and Communication Technologies, a sustainable development approach to certain projects can convert a city into a smart city, integrating aspects of governance, demographic and economic dynamics in a way that is appropriate to the concerned social capital. This case study of an Angolan municipality touches on the deployment of the use of indigenous knowledge and key tools in the drinking water sector, and discusses best practices for resource management, in particular towards water offered by nature to satisfy human needs.

5.2.4.1. A smart city in Africa: mirage or opportunity?

In the decades to come, the populations of developing countries will also aspire to live in cities that are said to be smart. The latter are characterized by their modernism and sustainability, but also by the interconnectivity of the services they offer. Modernizing a city goes through technological innovation. As soon we acknowledge that within the word “techno-logy” is the word logos, knowledge, over the word techné, this innovation can be integrated advantageously into a territory. On the flipside, it can act against it when the technological choice is not appropriate or able to take root on the natural or social capital of the territory being modernized.

In a number of sectors, like that of drinking water, African municipalities, in particular in Angola and the DRC, even though they are equipped with a number of technologies have been surprised more than once and had to inherit the negative consequences caused by their hierarchical decision makers, suppliers, or service-providers supposedly experts who failed to account for the social capital and the characteristics of African urban sociology.

Drawn in by a mirage that has failed to lead them to a sustainable smart city that they have been dreaming of, these municipalities were made into the recipients of public services that were losing their resilience and efficiency beyond the limits of criticality. Having pointlessly consented to colossal investments in high-risk technologies, they were then called in by their superiors to ask why the water system did not work properly. It is only after measuring the criticality of their failing water systems that the municipalities that were approached during this study realized that the answers to these questions could only be found by deploying a reliability metric each time they committed to installing a new water system.

In the Angolan case, the decision makers such as the users of the water services joined this study and agreed to assess the criticality⁶ of their systems in the hopes of producing an analysis of the situation that may enlighten them. After this, to quantify this criticality, the severity of various failings identified in said systems were multiplied by their occurrence and their detection, while accounting for a set of 36 parameters, spanning the five primary operations of a water supply system. The criticality of any dysfunctions in the water systems is represented in the histogram in Figure 5.7: the very high criticality numbered at 27.69 for the locality of Buenga Sul, 16.93 for Cambozo and 19.76 for Nova Esperança on a scale where the acceptable range is between 1 and 11, showing us that these systems have only maintained an identity-based resilience. By “identity-based resilience”, we mean a critical usage model beyond the normal capacity for resilience of a system.

They were unable to absorb any sort of disturbance, reorganize and continue to operate in accordance with the principle of sustainability and expectations of its users (which is an average delivery of 6 liters of water per day, per person). These results show us that just for the function “water”, a function that is highly critical in Africa considering that only 42% of the population has access to it, we are currently far from smart cities being a viable opportunity.

5.2.4.3. Towards a frugal “smart city”

The Angolan failures recorded in the three villages of Buengas allow us to propose a design model⁷ of eco-efficient water-supply systems for rural towns in developing countries. This model has generated three tools, two of which are managerial in nature and one that is technical. Among them there is (i) the criticality metric we mentioned earlier, (ii) the reliability index (ZOMBO Index⁸) as well as (iii) the blue pump, which is the frugal innovation derived from this research.

The model is characterized by the fact that it references the expectations of stakeholders based on the indigenous system of knowledge production, the functional architecture of said model, the physical architecture of a typical water system to implement. The critical elements taken into account during the creation of this model are those coming from the indigenous knowledge production approach under the Arbre à Palabres⁹ as well as the production, processing and distribution operations of water. The design approach we used for this model establishes specific objectives, creates a checklist of all possibilities and subsequently determines the requisite improvements for the definition and characterization of scalable models applicable to developing countries.

The index that results from the formula presented below (see Figure 5.9) is driven by an eco-design approach fed by 96 parameters considered as critical to a water supply chain due to be eco-efficient, able to prequalify any new water system prior to its implementation, as either very risky, risky or even conversely as a veto. What we call VETO is actually the limits imposed on our model by the complexity of its environment.

Of course, this formula used by researchers and engineers was translated into common vernacular allowing users to use simple questions relying on directly observable elements to assess the quality of the eco-design approach and the reliability of the system in place.

In Quipedro, a new location fitted with a novel water system eco-designed within a participative approach and thanks to a frugal innovation known as the blue pump, the level of performance reached by the water system is excellent. It is very reliable and operational 24/7. Fitted with environmental technology, easy to install and acquire, causing no pollution, boasting low maintenance costs and an approximate useable life of 50 years, without outflow of currency, this pump uses only indigenous resources. It would be one of the most precious gifts one could offer future generations of developing countries, in particular in rural cities, all of this within the limits of criticality.

In Angola, the study demonstrated that it is possible to optimize the performance of water services thanks to new technologies on condition they be sustainable and the use of water responsible. However, despite consented investments, the urgent need to update the access to water purification installations and intensify hygiene practices in order to extract as many advantages as possible from these services, remains. Here and for other villages in the Southern Hemisphere, the water sector remains critical, and requires sustainable technologies that will ensure large-scale distribution. In search of solutions adapted to local contexts, the authorities can call upon the principles of smart cities… on condition that they obey the principle of frugality¹⁰.

Nowadays (2018), Namibia is offering Dr Zombo Mussema a position as Professor at a top French University, to replicate the blue pump in the arid context of the country. The hydraulic motor of the blue pump will have to be replaced with a solar motor, possibly coupled with wind-farm technology, which is the local free energy in Namibia for extracting water from underground. As the pump is designed with modularity in mind, all that is needed is to invent a solar motor using the same principles: the blue pump will become the yellow pump, but the principles of eco-design will be the same.

5.2.5. Urban problem and economic transition: the Russian case of monotowns

Detroit in the USA, Turin in Italy, and Sochaux, Thionville, Florange and Le Creusot in France are – or have been – monotowns. These mono-industrial cities, with activities relying on a single industry and with residents that had only a single skill, are inherent to the capitalism of the second industrial revolution (1870–1971). The phenomenon is inherent to the silo-structured mass production model, where large companies are the common method of research for productivity increases. This production model has since become obsolete with the transition to the third industrial revolution that relies on technologies with a higher technological intensity, diversified with network relays of generally medium-sized businesses (even though sometimes they can remain organized around a single core company with a smaller size), and where innovation and diffusion of knowledge play a critical role.

In Russia, monotowns are born of both the capitalist tendencies of the authoritarian State that once was the USSR, the specificity of Russia’s social history and its historical and geographical contingences. They are created near prime resources in Siberia, in the Ural, in the Arctic, in an economy mostly based on primary activities. Some of them started out as gulags, such as Norilsk (located north of the arctic circle). They also resulted from the outsourcing of industries threatened by the German advance in 1941 when they were actually moved east (which at the time was a remarkable feat).

5.3.1. The power of data

Philippe Albrecht, a consultant and researcher, is an ace in data management, but not a geek hoping to build a paradise playing on his keyboard. Data are dangerous to manipulate, because it is playing with the peoples’ private lives and even their freedom. In his approach, he uses only data processing – Big Data – to control city management. This is not only to improve management, but also to predict certain events. This is a risky area, where gurus, often more powerful than Erik Schmitt, the CEO of Google, have perfectly understood that whoever controls the data controls the world. How can we develop a practice that does not infringe upon personal liberties and is limited to ends that are good for everyone?

5.3.1.1. Big Data and smart cities are intrinsically linked

Big Data is a catch-all term that can be compared to a four-stage rocket: data generation – capture and storage of data – data analysis – governance and optimization.

5.3.1.1.1. The 3Vs: Volume – Velocity – Variety, or the endless increase in data volume

The first stage of the Big Data rocket is exponential and quasi-endless generation of data by all manner of sensors that span all urban activities: energy consumption sensors (smart sensors, among others), energy production sensors and motion sensors – static sensors (cameras – railways) and dynamic sensors – in vehicles – smartphones. These incessant interactions, between men and machine – human to machine (HtM) – between machines – machine to machine (MtM) – are the main vector for this growth. The Big Data adventure is only just beginning: volumes will still be growing from the transformations in digital technologies and their new uses. The energy transitions, for example, will generate new applications that will increase complexity. Energies said to be sustainable (wind turbines, photovoltaic, biomass) in that they are intermittent can only operate when connected as a grid – a meshed relay of production networks – produce vast quantities of data. Amazon now makes most of its revenue from data-hosting than from online retail, and due to the energy cost of transferring data, it does it… with freight trucks. The snowmobile can transport 100 petabytes of data in complete security, and has armed guards!

The emergence of new roles for a population who are no longer just data-consumers, but also now producers through the use of networks such as smartphones, new consumption habits traceable with dematerialized payments and a finer mesh of territory networks by surveillance systems contributes to this continuous increase in the volume of data.

On top of quantity, there is variety in the sources, therefore new types of consumption such as electric vehicles, new types of charging stations in parking lots, garages and streets. In home automation, the IoT includes all connected household items, sensors (thermostat, smoke alarm, motion sensors, etc.). The data resulting from these objects are both more varied and more precise. They present data about consumption and volume production of fluids, energy, water and prime resources through time. Collecting flows from different networks now occurs in smaller and smaller timeframes and in practically real-time. Counting data is also diversifying: weather, typology of equipment, cartography, recorded alarms, etc.

5.3.1.1.2. Digital technology as a foundation

The second stage relies on digital. This broader, more complex, dense and faster information must be captured, stored and transported to be analyzed and governed. This is where the Internet of Things (IoT) is completed by the digital evolution and innovation. These growing volumes need to be stored and shared. Moore’s law is continually being verified¹⁶. Data are stored on increasingly powerful servers. It is moved around and shared via Cloud Computing that bridges the gap between storage and networks (the Internet, primarily).

The IoT is the backbone of the system

The Internet is the backbone of the massive exchanges of data that are produced and exchanged every second, every nano-second. In 2015, mankind produced as much data in a year as it had in all of history. Today, the total volume of data produced every 12 months doubles. Soon this will be the case every 12 hours. Very soon, we will count 3.4 connected devices per person. The IP (Internet Protocol) traffic will grow 22% every year between 2015 and 2020. This growth is primarily due to MtM (Machine to Machine), which will increase 44% per year between now and 2020 with 50 billion connected objects in the world, 40% of data on the Internet are now produced by connected objects. Three billion people will own smartphones; the whole market representing seven trillion dollars (associated objects and services). According to a recent survey, 84% of people in France stated that connected objects were a source of progress¹⁷. The Internet has therefore entered the physical realm. It is therefore no longer just an additional layer of the urban system but its very essence.

The digital industry is supposed to optimize our consumption of energy, yet so far it is on its way to posing even more problems of its own, but of a different nature than fossil fuels. In 2016, 1.5 billion smartphones were sold in the world. To achieve this, the industry used up to 12% of the world’s demand for gold, 30% of silver, 30% of copper and up to 80% of rare metals such as ruthenium or indium, the extraction and refining of which cause important environmental damage. Every hour, 10 billion emails are sent, which corresponds to 50 gigawatts of electricity, or the equivalent to 4,000 round trips between Paris and New York on a plane [JAR 17]. 750 billion mobile phones are thrown away each year, along with the highly toxic components inside them such as cadmium, lead, cyanide and mercury that are then sent to China, India and Africa¹⁸. In France, the data centers that process Big Data have used 10% of the electric energy produced. Digital networks and data processing are undoubtedly part of the solution to the problem of smart cities, but they are also part of a new problem.

5.3.1.1.3. Analysis and optimization

These two first stages are of interest only because they allow us through analysis and governance to accompany the evolution of the city towards optimization. Analysis and assessment are the third stage of Big Data. The importance of data in smart cities effectively find their meaning here. The logic of networks, collecting and processing information, and assessing and measuring their potential and their limits conditions the performance of these cities.

The interoperability of these data is at the heart of this analysis. Philippe Albrecht develops the tools that allow him to visualize and understand the operation and consumption of cities and distinguish the dysfunctions and extract from this information the needs for which we should be finding smart services and uses. Figure 5.12 shows how an electric relay manager that manages the accounts of 35 millions users collects data from a multitude of sources in order to predict events and optimize the network. Since July 2013, the fire department of the city of New York has implemented an algorithm that analyzes 60 fire-hazard risk factors [DWO 14]. The level of poverty in the neighborhood, the age of the building, the state of the electrical installation and the presence of automatic fire extinguishing devices are all part of the criteria studied. Similarly, a building that is vacant or unguarded has double the risk of catching fire. The 341 fire units in the city must inspect a total of 50,000 buildings every year. The algorithm in place establishes a risk score for 330,000 buildings and provides a list of priorities that helps the firemen during their weekly inspections that occur depending on the risks identified.

The conditions for success lie in the interoperability of data, that is, access and sharing of data via standard formats (including APIs¹⁹). The issue involves making data available in a format that is legible and usable for operators, which supposes building a dictionary of data to give them the same format, and a syntax, or grammar that will define how to process them. Thus, the appearance of a new position, which will be critical for tomorrow’s cities: Chief Data Officer. Will the control of data be granted to machines or to a company or to the city? Behind this technical conundrum, lies a political challenge.

This issue will grow in relevance with one of the big technological breakthroughs that will help extract the quintessence of Big Data, which is the development of Artificial Intelligence. The latter has the capacity to perform analyses and draw conclusions via large-scale algorithms. Machine learning goes even further allowing for self-teaching via the recognition of recurring models (or patterns) and increasing the depth and quality of its optimization.

The stakes for cities are colossal

Let us take the example of the operation of public operators in cities – waste and sewage management, maintaining equipment in working conditions, planning the activities of municipal agents, maintaining parks, etc. According to a study by Mckinsey dating back to 2013, one trillion dollars in savings can be achieved in cities worldwide by optimizing public infrastructures. In fact, the investment towards responding to urban growth between now and 2030 is estimated at 57 trillion dollars²⁰. We understand that, over the next 10 years, we could be spending 10 trillion of that amount, while optimizing the city’s operation as well as its efficiency and adaptability. To understand the magnitude of these numbers, let us remind readers that the global GDP is somewhere between 100 and 150 trillion dollars, depending on how it is counted (source IMF). Look at water, for instance. In 2013, 60% of domestic water use was in cities. Yet, 14 billion dollars a year are lost due to water leaks or wrong billing. Another essential element of the city is transportation: humans cover a little over 30 billion miles per year to date. It is expected for this number to exceed 150 billion in 2050. At the same time, it is estimated that drivers spend 50 hours a year on average due to delays from congestion in cities.

Artificial Intelligence would be a major rupture

AI will allow us to precisely identify these malfunctions and take rapid adjustment measures. We can cite, for example, the French electricity provider Enedis that has fitted its network with IoT sensors to analyze dysfunctions on the network and optimize interventions (Figure 5.5). In the case of optimizing transportation in the city, we can look at Waze that is an app that indicates to drivers the optimal route depending on traffic density. This density is calculated primarily thanks to human interaction. Drivers indicate ongoing events on their trip and the algorithm calculates optimal routes in real time.

5.3.1.1.4. Decision-making and governance: distinguishing between short term and long term

The last stage of the rocket is decision-making. Here we must separate immediate operational decision-making, or in other words, how we can influence and govern in real-time and semi real-time (the example of Waze or Enedis) the decision to invest or to plan, which have long-term consequences.

Real-time governance and fundamental split

AI applies well to operational governance, because it relies on the analysis of repeating processes and behaviors. Thanks to Big Data, the city can be governed to manage permanent optimizations: balancing traffic, energy consumption and production. In cities and territories that function or that will function on the same objects on multi-energy and multi-materials, where production is increasingly decentralized, the ability to permanently adjust towards the equilibrium between supply and demand will provide phenomenal performance gains (as explained above). For the first time on a volume and complexity scale that currently has a seemingly endless potential for growth, we are seeing the appearance of a permanent feedback loop between bottom-up (information going upwards) and top-down (decision going downwards). The datum (and therefore the machine) governs our reality.

Luis Bettencourt tells us the story of the unexpected discovery he made during a conference at CalTech (California Institute of Technology) [BET 13b]: attending a conference on connected vehicles, he spoke up to highlight the importance of taking into account the human factor. “No need”, answered the CalTech researchers. The problem with human decision-making is that it occurs in timeframes in the order of the second whereas machines operate on feedback (the time between perceiving a situation and taking action) that is in the order of the millisecond. It is therefore more reliable to let the machine handle situations as long as the situation encountered is supported by the system. Under certain conditions, concludes Luis Bettencourt, you do not need to be very smart because simple automated situations can solve very difficult problems. In certain situations, as long as all the parameters are integrated into the model, which is de facto impossible outside of a controlled environment, human vigilance will no longer be required.

Long-term decisions can be optimized by predictive systems

Long-term decisions, however, mean imagining, trying, testing and adjusting. AI is no longer enough in this space and human intelligence is predominant. Predictive models help seek efficiency (the result) and effectiveness (the means used) of private, public and mixed economic decision-making. They respond to fixed objectives that can be qualified as optimal, keeping in mind that these optimums are inherently temporary and do not represent an optimal equilibrium. For example, if we look at the perspective of public decision-making in the service of the city, the following optimums could be created:

• – development of the economy and employment;
• – increase in fluidity of mobility;
• – optimization of energy consumption;
• – response to population increases or dips;
• – transition towards new economic models, etc.;
• – the starting or mature state of what already exists;
• – restrictions, financial ones, for example (investment capacity, indebtment, balance between l’OPEX/CAPEX, etc.).

Visualization tools facilitate decision-making

Lastly, visualization tools are the final layer that help facilitate decision-making ergonomics. PRECARITAIR (Figure 5.6), developed for EDF, helps target areas of energetic poverty and target the impact of tariff variations over the solvability of populations. This tool also helps orient renovation and isolation policies of buildings in order for it to profit the poorest.

Mass data processing therefore allows predictive action at a low cost both in terms of operation and more importantly in terms of impact over society. Big Data will therefore be of great help towards understanding the dynamics of dissipative systems (human systems) that are not accessible to the laws of physics. Data processing will help understand in broad strokes how a social system behaves, how a human system behaves, a city, a neighborhood, and those broad strokes understandings will be enough to act on a system’s dynamic.

Philippe Albrecht develops tools that will allow us to visualize and understand a city’s consumption, its operation, as well as discern any dysfunctions and outline from this information whatever needs should be addressed with smart services. He has taken the initiative of providing a new angle to the discipline, a frugal one, using the best aspects of OPEN DATA and OPEN SOURCE.

5.3.1.2. From open data to predictive data

Open data is the public counterpart of Open Source. It is information made available to all for free use. It is a common good. Public open data is spreading rapidly in France, under the impetus of the INSEE that makes a large amount of data available to the public, the precision and the value of which are highly underestimated. For example, the electricity billing regulatory law (or TURPE) insists on the goal of transparency towards operators in this sector, that user-data pertains to the consumption and transport of electricity be made available on open-access platforms.

5.3.1.2.1. The knowledge of wealth comes from cross-data referencing

Companies have started pooling together their data on specific subjects, knowing that sharing this information will be more beneficial than keeping it to themselves. Take a look at the example of the Avere-France, an association that gathers all industrial, commercial and institutional stakeholders in electric mobility: manufacturers, distributors and maintenance professionals; equipment fabricators, energy experts, installers for batteries, charging systems, components, etc.

On this basis, Philippe Albrecht and his company PCG have created an innovative application based on a simple idea: placing oneself in the shoes of a sporting equipment vendor. It relies on three sources of information: static data of open data that provides a distribution of population based on their age, profession and family status. Dynamic data, collected from smartphones, credit cards and all other sources, and lastly, predictive data that are the result of cross-referencing the data from the two previous sources. The quality of predictive data improves over each predictive cycle and can tell us how people get to the gym, allowing businesses to place billboards and advertising materials on their route. If, on top of this, we can find out at what times they will go past this billboard, and on which days, targeting can be even better. Thanks to Open Data, we have catalogs of products and their prices, and we are then capable of valuing the route. Philippe Albrecht’s teams have developed a product – SPOOK (see Figure 5.14) – that helps favor the potential revenue that can be made on the different routes depending on the product we want to sell.

In the screenshot above, we can see the value of people’s movements in Paris depending on their ability to buy climbing equipment. The points represent sporting installations. The thickness of the line represents its value and, in this case, the purchasing potential. We can see the potential that this app can provide, if we want to manage other types of activities like security around stadiums, channel flows of supporters during large sporting events. Collectives manage tourist flows on tourist sites from data gathered from smartphones that give their nationalities and tell them how they move around. Static data of open data provide statistics on tourism habits, in a way that their trips can be improved. From open data, we can develop territorial nano-targeting to target precisely, to within a street, the value of a geographic point, depending on who uses it, where they are coming from and where they are going. From Big Data to big brother.

We can never talk about Big Data without touching on cybersecurity, something that is now a full-on discipline of the smart city. From security and confidentiality of data and the political independence of a city, the stakes are considerable.

The Snowden case showed us how a government can surveil its citizens with considerable means, in this instance, the NSA (National Security Agency). Under the direction of General Keith Alexander from 2005 to 2014, the agency decided to “collect everything”, including digital communications, to know everything about everyone, in the name of national security, obviously. These practices were revealed to the world by Edward Snowden, who was subsequently forced to leave the USA, along with journalist Glenn Greenwald, who gave a detailed account of the NSA’s practices [GRE 14]. The NSA made confidential agreements with major social networks and search engines to access their data. It adds its sources to the control of digital traffic on communications networks to intercept emails, any phone communication, anything going through a wired connection. This was called the PRISM program (Figure 5.15): everything is intercepted, analyzed by powerful machines capable of drawing links between data that are meaningless by themselves. In principle, the access to messages is protected, but not the access to the metadata. For example, a machine will detect that Mrs. X called her lab to receive the results of a test, then Planned Parenthood, then a man who is not her husband. We can immediately detect an affair and a critical situation that can give an opportunity for blackmail.

The NSA, FBI, CIA and even the DoJ (Department of Justice) work together to achieve political objectives for the US government, and will share data with corporations when their interests are at stake. This is used in an example of American extraterritorial law. An email passing through a server located on American soil was enough to grant the DoJ the ability to investigate the activities of said company and subject it to an investigation under anti-corruption laws and have access to all of its data. This is how GE took possession of Alstom²¹.

A cold war is ongoing on digital networks. The United States are working in close proximity with Canada, Australia, New Zealand, the UK and have close partnerships with twenty other countries. On the other side, the Russians and the Chinese are developing their own strategies.

It is not just about intercepting data: the NSA can implant malwares on any device and control how its owner uses it, by reading keystrokes, or even infect it with a virus that will block the information system. Digital security is therefore a considerable issue when talking about resilient cities. Cities often do not have the necessary abilities to undo all of these traps and build cyber-security systems, which requires collaborating with central agencies, such as the ANSSI (Agence nationale pour la Sécurité des Systèmes d’Information [National Agency for the Safety of Information Systems]) in France.

5.3.2. How much do smart cities cost?

We saw in Chapter 4 the case made by the American Association of Civil Engineers on the cost of obsolete infrastructures in the USA and the benefit that stem from modernizing them. Their costs, from then on, are no longer costs but rather investments, as long as we account for derivative impacts, the positive and negative externalities. We saw in Chapter 4 how the American Association of Civil Engineers calculated the cost of obsolete infrastructures and the impact of renovating them, which surpasses the costs by far. Those costs then immediately become investments that add value. For Phil Banes, Director of smart city council, a group of producers that consult for cities on their investments, smart cities won’t cost anything if investments on digital technology are performed wisely by integrating technological building blocks during large urban renovation projects.

In the externalities, there is not only the cost of obsolete infrastructures, but there are also other externalities such as pollution, stress, energy and waste. We know that the larger the city, the more the waste, pollution and stress it produces and that its energy consumption grows proportionally to its size.

Figure 5.16 shows the relationship between a city’s size and the growth in stress and their derivative ailments. We find here the conclusions of Paul Bairoch on the optimal size of a city being below 200,000 habitants. In Mexico Ciudad, where there are 21 million people, the average time spent in public transport is four hours, supposing that 10 million people are commuting, which makes a combined 40 million hours wasted every single day. These hours can be converted to work not being done, pollution, stress and less time with family. This spoilage of social life is inevitably reflected in crime stats throughout the city.

As early as 1920, British economist A.C. Pigou suggested taking into account externalities into cost calculation. This is desirable as long as we can establish a city’s accurate total costs.

Let us look at the example of waste: in 1925, economist Stuart Chase described the phenomenon in The Tragedy of Waste, not only from a economics perspective, but by questioning a number of social sciences that were outside the production sphere and that needed to be accounted for beyond direct costs in terms of wasted time, wasted produce and quality of life, in a way that reflected the inter-relations between products and waste. Waste production was at the heart of the production model during the second industrial revolution. In 1924, the Phoebus cartel, an oligopoly uniting incandescent light bulb manufacturers, launched the idea of programmed obsolescence effectively shortening the lifespan of their bulbs from 2,500 to 1,000 hours. Oil companies along with Renault in France, General Motors in the United States, torpedoed electric street car systems in order to replace them with buses. Waste production was becoming the key to the economy denounced by Kenneth Galbraith in The Affluent Society [GAL 58]). Limitless urban expansion in the USA, analyzed by Lewis Mumford, becomes a black hole of consumption of automobiles, energy and pollutant products. With globalization, it is a more insidious form of waste management that settles in accordance with the theory of Lawrence Summers, according to which it is more rational to pollute poor countries than rich ones.

China became the most polluting country because it based its growth on becoming the northern world’s workshop. Today’s tragedy of waste is in dissociation with areas of production – in poor countries – and consumption – in rich countries. The sincerity of costs command that negative externalities generated in poor countries be taken into account.

In the case of digital, that we present a technology that is fundamental to solving these problems, which is in turn seen as clean technology with its white rooms and its immaterial aspect, the situation is even worse. Producing digital technologies is consuming rare earth minerals, which require a lot of pollution to produce. Bernard Tourillon, director of Uragold, a company that produces materials for solar energy, estimates that the production of a solar panel for an individual generates 70 kilos of CO₂. Are electric cars the solution? Building one of them requires far more energy than a fossil fuel automobile due to the weight of lithium ion batteries [NEA 15].

Journalist Guillaume Pitron wrote an article about the production of rare earth minerals that demonstrate their prohibitive costs and the catastrophic impact of their use [PIT 18]. China has renewed its rare earth mineral strategy of sub-contracting waste from the West. Not only does this allow rich countries to pollute without care, but it also allows them not to have to think about how rare earth mineral waste is recycled, an operation that is difficult and costly, meaning that only 10% of rare metals are recycled today. Green cities thanks to digital technology? A considerable increase in pollution and the production of waste above all else.

Transport is at the source of considerable external costs. In France, the ADEME assesses the drop in life expectancy linked to exposure to fine particles to be of 8.2 months. According to the OMS, pollution due to particles is the cause of on average 6% of premature deaths in France, half of which are attributed to traffic emissions. The latest scientific studies reinforce this link between pollution in the air and breathing and cardiovascular diseases and evidence effects on our ability to reproduce, as well as fetal and neurological development. Nitrous oxide (NO₂) and ozone (O₃) also prove to be toxic for humans and to have negative effects on our ecosystems. The health costs (premature deaths, chronic bronchitis, etc.) of pollution represent each year between 20 and 30 billion euros in France. Add to this, the cost of wasted time and of stress.

Electric vehicles may appear at first glance as a solution, as they emit only 32 tons of carbon from factory to scrapyard, which is half of what a petrol car would. However, its production consumes three to four times more energy. Overall, throughout the car’s entire lifecycle, an electric car produces three quarters of the pollution of its petrol equivalent, and this is when talking about a car that must be recharged every 120 km. With Tesla announcing that their cars have an autonomy of 800 km, the advantage of electric cars are going to decrease even further. Texan lawyer John Petersen, is quoted by Guillaume Pitron, who has built a career in the battery industry as concluding “electric vehicles are technically possible, but their production will never be sustainable from an environmental point of view”, which is the same conclusion reached by the ADEME “over the course of its lifecycle, the energy consumption of an electric car is overall the same as that of a diesel” [ADE 16].

Here, though, all externalities must be included in the costs. Where does the electricity come from? What will be the impact of recycling a large park of electric vehicles? Is a city that forbids automotive circulation in its city center just “shoveling snow into the neighbor’s yard²²”? Calculations performed by the research center Energie demain highlight the location of the source of the pollution linked to commuting (Figure 5.17): French city centers may appear green, but this is only because pollution is moved to the outskirts. We have seen the impact of gentrification phenomena on housing prices in city centers, to make room for the “creative classes” and their cycling lanes.

In Paris, it is forbidden to drive along the banks of the Seine. This translates to an increase in pollution, in particular along the highways around Paris, on the Eastern side, in the lower income suburbs. Drivers using the river banks are mostly crossing through the city and do not actually live there. In exchange for a minimal decrease in pollution in the immediate vicinity, the Airparif association [AIR 17] has found that we are seeing a high increase in pollution all the way along the traffic veins (Figure 5.9).

This is an expression of a law of architecture of complex systems: over-optimizing a function leads to under-optimizing the overall system. Building pedestrian streets will have an impact on the direct environment, but if we want to gauge the global impact, we need to look at the impact on the overall circulation flows.

What is the conclusion? There is currently no golden bullet for ending pollution. Common decency says that we have to account for exported pollution linked to production. There are nascent technologies that would help produce in more eco-friendly manners, such as small modular reactors that can be developed in short amounts of time and produce 300 MGW, which is enough to power a small town and its outskirts, and with a waste production of 4% of that of a classic reactor, and a short lifespan, and almost no waste in the case of thorium reactors. Smart cities remain in all aspects fodder for innovation.

The cheapest and least polluting energy is the one we do not use. We can act to reduce the transportation time and therefore the pollution that goes with it, as in the case of commutes. They grow proportionally to the size of the city, in the urban Parisian area; it is the order of 70 minutes (Figure 5.19). Beyond 1 h of transportation, fatigue can be felt and impacts working conditions. Note that fatigue is mostly experienced by people using public transport [MIN 15].

Reducing time spent in transport can be done in many different ways. The first is to control the price of housing in city centers that is shooting up under the effect of transport networks. In NYC, all networks converge towards Manhattan, which contributes to skyrocketing prices. This is the case in Paris as well, where prices are linked to proximity to transports. Gentrification policies that led to the working classes being driven out to the outskirts contribute directly to increasing transport times, as well as the suburbanization phenomenon, which leads executives to look for houses with gardens outside the city at the cost of a longer commute. As was suggested by urban designer Jan Gehl, the key is therefore to control the housing prices by starting with property prices. In tourism-driven towns like Chamonix, property prices have increased so much that the city can no longer afford to host the personnel it needs to operate the tourist installations, which then contributes to the increase in circulation in the haute vallée de l’Arve.

The other element is work organization. The photo in Figure 5.20 presents the corridors of the French Ministry of Finance during the middle of the work day. Every employee is in their own office, with no contact with other employees outside of the lunch break, for those who eat together. Offices are organized linearly along long anonymous corridors. The neo-Stalinist architecture of this ministry reflect the work organization of the second industrial revolution; one that values mass production and requires standardized isolated tasks and a central production of energy that means aligning work stations and no communication between employees. In his patterns, Christopher Alexander had already identified the possibility of distributing work in a variety of locations, something that is all the more possible in the age of digital. This is different to teleworking, which would not solve the problem of worker isolation and would not respond to security standards for the tasks in question, but rather to design communicative workplaces.

In conclusion, any architectural and urban planning decision involves costs in terms of transport, energy, pollution, waste recycling, stress, public health as well as increased synergies that they encourage. Reasoning in complete costs that integrate the externalities, an idea started by A.C. Pigou in 1920, will be a necessity when public management undergoes its inevitable restructure.

5.3.3. The government of a smart city

As early as 1613, Neapolitan Antonio Serra, in a memoir presented to the Vice-Roy of Naples, “on the causes that allow an abundance of gold and silver in kingdoms that do not have mines”²³ maintains that there are activities that are more productive than others and formulates the principle of increasing returns in the industry, linked to the development and freedom of cities. Serra is in fact the first to have formulated the principles of an “industrial policy”, where the state directs the economy towards activities with higher added value, following the principles of cumulative effects relating to learning, something that the theory evolution will reuse under the concept of “technological path” trajectory phenomenon. Serra ended up in prison, his work being considered irreverent by the Viceroy – and Southern Italy remained feudal and never followed the route of industrialization that the North did with its flourishing cities.

Economic development is linked with the harmony of urban life, where economic activities can enter in synergy and where the dynamic equilibrium and the evolution of the city are ensured by a government driven by the ideal of common good and classic wisdom as represented in the murals by Ambroggio Lorenzetti on the town hall in Sienna (Figure 3.2). The increasing complexity of cities, their dysfunctional developments and the predominance of top-down urban planning have made us forget these strong principles. In an analysis of ongoing smart city initiatives, Italian researchers united around Paolo Neirotti of Torino’s Politecnico [NEI 14] found that there is none that embraces all fields, physical domains, transports, natural resources and energy. The city’s government and administration will not necessarily be a smart system of life. In fact, teo models emerge from the Neirotti study, one is technocentric, heavily pushed by technology vendors, and the other based on the people, but the technocentric is dominant.

The problem is that the technocentric approach is upheld by corporations with efficient marketing strategies that, unfortunately, work. In addition, there are no vendors of good governing, quality of life and civic life; this is an issue because the systemic integration of the city relies on this ability for people to appropriate technological systems and make them serve their purposes. The social capital is the inevitable base on which the technical capital must take root if it is to truly contribute to the emergence of an urban intelligence.

One of the remaining tasks to undertake is to grant our political figures a practical and methodological baggage for integrating these two types of domain.

5.3.4. What are the tasks and what is the form of a smart government for a smart city?

A city is first and foremost a place where economic opportunities are created. This occurs through synergies between activities, and therefore between people. Public policies can favor – or block – the conditions for their creation. They develop naturally when civic life is active. The rise of the digital sphere has meant that people must be vigilant to ensure the validity of an investment, assess local and foreign pollution, and demand transparency to avoid corruption. These are subject truths presented as established or imperative to public debate. Digital opens new fields to innovation and a new role to the user that must be favored for two reasons: creativity and validating social utility and innovation. We have demonstrated abundantly that smart cities are political projects above being technical ones. Experiences past and ongoing show the importance of popular participation, which makes direct democracy a viable government model.