Smart city has become a loaded term – earlier Smart City projects were often expensive, didn’t fully deliver and embedded top-down models of centralised control in city operation.
However, the term is still widely used as shorthand to talk about the use of technology in cities.
In the time since the first projects emerged there have been developments in technology, but also changes to the wider social, political, environmental and economic context.
2020 lead to a re-evaluation of many accepted norms, making now a good time to consider how we respond and simultaneously think about what we want our long-term future to be.
Technology will play a key role in supporting this future, leading to the question of what is a smart city?
What is a smart city?
A Smart City should use technology to make cities better for people.
In order to make things better, we need to understand in more detail how they work now, so that we know what to change.
What this means is using technology to better understand how our built environment enables and supports specific outcomes over time. These outcomes are the cumulative effect of day-to-day behaviours repeated for many months and years.
For example; driving to work every day is associated with higher risk of negative health outcomes (including obesity), worse air quality, more congestion, higher carbon emissions etc.
What is becoming increasingly well understood is the role of the built environment in encouraging these behaviours – for example the way that streets, land uses, densities and public transport can make it possible or impossible to walk. Without understanding the limitations of the environment we’re locked into, it can be very difficult to change daily behaviours and influence long-term outcomes.
What are the outcomes?
There is evidence of a shift in the outcomes we prioritise, with economic and financial outcomes being joined by wider social and environmental considerations.
Enabled by social network platforms, and accelerated by Covid, a series of issues-focussed global communities have shaped public debate and policy:
- extinction rebellion and the climate emergency
- black lives matter and racial discrimination
- the culture wars, inequality and polarisation of political views
Delivering long-term outcomes requires policies, strategies and plans being developed now, that can set and coordinate responsive actions. These public conversations have happened concurrently with the adoption of policy and working practices that show a change in emphasis:
- Around 75% of England’s Local Authorities have declared a climate emergency and are developing road maps to reach zero carbon.
- The Welsh Assembly adopted the Well-being of Future Generations Act, stating that all decisions be made taking into consideration the potential long-term impacts on future generations.
- Voluntary reporting on UN SDGs have been adopted by many cities, including London.
- The NHS has adopted a long-term strategy based around prevention, place and the use of technology.
This raises important questions:
Who should define the outcomes we work towards?
Should Central Government Politicians be elected on the back of a long-term vision, and how will outcomes be affected by potential changes to government midway through implementation?
Should Local Councillors be elected on the same basis, and what happens if their vision for a local area is not shared by, or consistent with a centralised view?
Should politics be excluded from these decisions, with choices made by unelected experts who define outcomes on the basis of what delivers the most balanced positive impact, or what follows global best practice?
Should local communities and stakeholders shape these on the basis of local knowledge and commitment to an area, but potentially without domain expertise?
Should a potential set of outcomes be set out and voted on locally?
These are complex problems to resolve, but they highlight that for cities to start to deliver better outcomes, wider systemic change is also required. Perhaps technology can stimulate this change by enabling data-driven policy, or rapid impact testing of scenarios, to widen the conversation.
How do you deliver positive outcomes?
Cities, or interventions in cities, go through many stages; policy, planning, design, construction, operation and maintenance.
Earlier generations of Smart solutions focussed particularly on operation and maintenance stages. For example managing city traffic lights on the basis of live traffic flow data.
These types of solutions can improve things – traffic may flow more freely for example, but these solutions will not fundamentally address the reason why so many people are driving at that specific time, in that particular place.
These solutions can be really useful to collect data on what is happening, but this is only half of what is needed. In school science, this data is the result of an experiment.
To understand why something happens where, needs not just technology solutions but domain expertise to understand the way that cities work.
It requires thinking about cities as a set of systems, then being able to analyse how each system works in isolation, and in combination with the others. These are the variables of the experiment, and we can now model and predict these interactions so that we don’t need to build things to see what happens in real life.
There is also the complication of adding people into these systems! It may be possible to see parts of a city that are car dependent, or poorly served by social infrastructure. These may not directly affect the lives of some people, but they do make it harder for older, lower income or less mobile populations to get to the things they need.
Technology makes it possible to use aggregated, anonymised data to see where there is a more vulnerable population in a worse area, and this knowledge can be used to prioritise interventions and specify improvements.
Cities are complex, and we won’t be able to understand exactly what happens everywhere all the time, or how the specific characteristics of one individual affect the outcomes, however what we can do is say where the environment makes things possible.
This creates three possibilities:
- Design better new places that enable different behaviour
- Identify existing problem areas and target a physical intervention in response
- Identify how to mitigate existing physical conditions through soft methods
Do wider systems support this?
While the technologies to support this approach exist, and have been applied to real-world projects, they are net yet widely adopted. For this to happen, the technology needs to really work within the constraints of the wider systems, and apply a suitable business model.
The problems associated with disciplinary or departmental silos are widely known with professions talking different languages, using different data and tools. Often detailed projects are developed on the basis of best practice, but fail to deliver intended outcomes. Furthermore, the impacts of, for example, a transport project may be felt by another department such as public health.
In many cases, departments share the vision to deliver a positive outcome, but lack access to the strategic level tools that enable them to coordinate and integrate with each other.
Detailed project implementation is still required, but needs a coherent startegy to combine multiple projects in different domains.
Often the problem of silos is reinforced by the allocation of funding to policy then projects. Perhaps outcome focussed funds could help address this, and encourage cross department working.
While there have been recent examples of this type of fund (e.g. shared outcomes fund), often the methods to assess funding applications are defined and executed by a single department (e.g. DfT), or state that an intervention must follow a set of predefined national guidelines (which may not respond to local characteristics of place).
There are also difficult questions to address around human resource, staff skills and disciplinary cultures. Building capacity to engage in new ways of working takes time and needs coordination with further education, professional institutes and employers.
Are these technologies available?
While it’s clear that wider systemic change is also required, the technologies for strategic, system-level thinking already exist:
- High-level, data driven, decision-support tools have been developed.
- Easily accessible web-based, community engagement and consultation tools are available.
- Data on city systems and outcomes is published.
Unlike earlier Smart City solutions, many of these have been developed separately by individual SMEs or organisations. Instead of creating a comprehensive, one-size fits all solution that is expensive and potentially difficult to adapt, future smart city solutions may be better formed from of an interoperable ecosystem of complementary tools and datasets.
Digital Twins have also progressed rapidly in the last few years, with a national strategy set out by the CDBB. Digital Twins typically focus on operational stages of implementation, and while understanding these impacts should help shape a design, the questions being addressed during policy, planning and design do not require the same level of resolution to answer, the same software model, or processing power to answer. However, it is still highly beneficial for them to be able to share information.
Enabling smart city eco-systems therefore requires more digital siblings than twins – they share DNA, and are able to speak to each other, but do not require the same depth of data or processing power to update. The Gemini principles set out by CDBB set in place some of the high-level standards to deliver this approach, which aligns with the idea of the eco-system.
Smart City 2.0
In response to the issues of the original smart city projects the term Smart City 2.0 has emerged. These solutions focus on delivering outcomes including societal benefits, informed by and open to intensive community engagement.
Technologies exist to deliver the vision of the Smart City 2.0, and to support the delivery of long-term outcomes. For these technologies to deliver their potential they require an aligned wider policy context, multi-scale system of decision making, and improved awareness and skills around this domain.