This guest post is submitted by Mischa Dohler - Chair Professor at King’s College London, Board of Directors at Worldsensing, Distinguished Lecturer at IEEE, Editor-in-Chief, ETT
“Smart Cities” – a trendy phrase likely to be hackneyed before even having achieved anything tangible in improving urban living conditions. Consultants, policy makers, think tanks – they all paint a rosy future for and through these smart cities. However, there are a few of us out there who are actually sweating to make cities smart. Today. What follows, is a review of some of the challenges we face as of the design year 2013, where focus is mainly on the use and deployment of smart city infrastructure rather than social, citizen and many other aspects.
Designing smartness into cities requires some major infrastructure upgrade; in a sense we are constructing the brain of the city. We have undertaken something similar before: we have built highways, the Internet, the Smart Grid. These prior connectivity exercises have two things in common: i) they have meshed and connected entities (computers, cities, etc) to the point that connectivity is secondary whilst the ability to provide services (FaceBook, supply chains, etc) has become prime point of interest; and ii) they were built without a specific nor proven return-of-investment (ROI) model in mind, with all of them having returned their investment by orders of magnitude. These connectivity initiatives however differ in one critical point compared to smart cities, in that they had significant governmental support which allowed them to become operational fairly quickly. Cities worldwide are inherently broke and governments historically don’t want to interfere too much with cities, the result being that there is very little financial support to making smart cities happen.
The biggest challenge of this early part of the 21st century is thus to bootstrap the undoubtedly high-potential smart city market in cities which are essentially broke.
To this end, I would like to share some hands-on experiences which we gained traveling around the world, knocking on the doors of cities and infrastructure providers, with the aim to generate business for Worldsensing, a company I cofounded and which is the only SME mentioned in Pike Research as a Smart City Pioneer, along CISCO, IBM, Vodafone, etc. During these travels, I figured there are roughly 3 types of cities: 1) ROI-driven; 2) carbon-driven; 3) vanity-driven. As for 1), the aim of rolling out smart city technologies is to generate income which pays for its deployment and more. There are many cities in the western hemisphere which fall into this category, such as Los Angeles, London. As for 2), the aim here is to reduce the carbon footprint and ideally become carbon neutral long-term. These are mainly cities in Middle and Northern Europe, such as Luxembourg, Helsinki, etc. Finally, “vanity” driven cities are mainly driven by events where the entire world is watching and they want to be perceived as “modern”.
The sales pitch in all three city types is of course very different. Take the example of smart parking, which is one of the product lines of Worldsensing: in 1), we sell the business process behind the system which is able to spot infringers who have not paid their parking ticket; our ability to guide people to vacant parking spaces was rarely discussed during the sales meetings. In 2), we sell the ability of the system to guide drivers quickly to an empty parking spot or advise drivers that certain areas are completely full, thus reducing unnecessary traffic, traffic jams, and thus pollution. Our ability to fine citizens had to be kept very quiet. In 3), whilst budgets are often not a problem here, the deployment rarely went through public procurement which required a technical and vision alignment with the prime partner for the smart city project.
Based on these insights, I would like share around 10 major challenges we faced, as well as some recommendations on how to go about them:
1) Political Cycles:
a. Observation: No matter how beautiful and useful your product design, most of the things you sell into the city will go through some form of public approval or procurement. The problem is that these procurements are, in many countries around the world, heavily coupled into political activities. In Spain, for instance, there are the city elections, the regional and the government elections: plus/minus 4-6 months of each of them, the political, and thus executive and with it financial firepower is completely paralyzed. If timing is unfortunate, this can leave you with only a 20% sales window opportunity. Can smart city business thrive under these conditions?
b. Recommendation: We need governance mechanisms at city, region and national levels which decouple the political cycles from the technological ones, and thus facilitate a proper uptake of smartness.
2) Political Decision Taking:
a. Observation: Since there is virtually no precedence of large scale smart city rollouts, decisions to use, or at least to trial new technologies, are very political in the sense of personal relationship to town halls, political agendas, etc. That is not a good turf for smartness to grow.
b. Recommendation: We need to ensure deployment mechanisms, even for early adaptors, which are based on fair market drive and associated competitions. Similar to what happen to the IT industry some decades back, we must decouple the political element from the technological one, where choosing a smart city technology ought to be as straightforward as to choose a new computer.
3) Intelligent Procurement:
a. Observation: Most of the smart city technologies will need to rely on a procurement process. Procurement today, by its very essence, chooses the set of technologies which fulfils the minimum requirements and then chooses the cheapest one. This is of course recipe for failure and certainly does not allow for sustainable growth and implementation of smart technologies.
b. Recommendation: Enforce mechanisms which meaningfully evaluate the future capability of the technology under consideration, and not only base the decision on pure pricing. We thus need to shift from a cost-driven approach to a longterm-purpose driven procurement approach.
4) Lack of Finances:
a. Observation: The lack of financial power of cities is very visible, and very problematic. In the ROI-driven cities and economies, there is a strong feeling that the only way of getting smart cities going is to properly bootstrap the market.
b. Recommendation: One solution is to concentrate strictly on ROI-healthy solutions, and there are some of them in the smart city context. Examples can be found in transportation (smart parking e.g.), smart street-lightening, or smart bins, etc. Another important shift which needs to be invoked relates to the change from CAPEX-driven city deployments to OPEX-driven approaches; the paradigm here would be a Smart City as a Service (SCaaS).
5) Established Stakeholder System:
a. Observation: Unlike common believes among the newcomers in the smart city community, the city space is serviced by a very established stakeholder system. It is run by companies most of us have never heard of, but these are companies which mainly provide the infrastructure, i.e. the visible part of the city. They are not the stakeholders which provide the intelligence, i.e. the ability to make the city really smart.
b. Recommendation: Ensure there is a real dialogue between the established stakeholders and the emerging stakeholders without the former feeling threatened about their space and without the latter believing to be able to do it all alone.
6) City Legacy System:
a. Observation: Cities are thousands of years old. Arguably the biggest technical challenge in any smart city endeavours is to retrofit smartness into these cities with a strong political, cultural and technical legacy.
b. Recommendation: We ought to make sure that smart city solutions are not only perfect standalone ideas and products but are actually being able to be deployed and retrofitted. That is, not only pursue design for a perfect end-purpose but make sure you know of the exact steps of getting it out, deployed and used.
7) Complex Eco-System:
a. Observation: Cities are extraordinary complex in stakeholder composition and interaction. To get anything meaningful done, also at global scale, under these circumstances is an arduous task.
b. Recommendation: It is not the first time that we faced the design of such complex systems with global footprint. Systems the design of which succeeded had typically undergone these processes:
i. Standardisation: It plays an important role in ensuring scalable up-take of technology, inter-operability, fair competition, and long-term availability. Therefore, smart city technologies ought to inherently be standards compliant. First global initiatives on smart city standardisation are well under way.
ii. Virtualisation: Often overlooked but it plays an important role in properly decoupling different stakeholders which in turn facilities independent growth in each eco-system. The computing industry has shown the way, where the hardware, operating system and application software ecosystems have evolved independently whilst always ensuring operability. Similarly, it is important to ensure that the smart city hardware, software and service applications evolve as independently as possible.
8) Urban Fabs:
a. Observation: The good news for the UK is that manufacturing in China is not anymore a difference of 1:10, but rather a 1:2 for medium volume product quantities. Manufacturing is thus naturally returning to the Western hemisphere. Urban fab labs, i.e. the production and manufacturing through e.g. 3D-Printing done locally, is a trending development. The problem is related to an increase of pollution in these areas, poorer waste recycling ecosystem, and the inferior supply chains of raw material.
b. Recommendation: As with supply chains and many other verticals, a virtualisation to manufacturing might be worth studying and considering, where – instead of dismantling them – macro manufacturing sites are shared in a cost efficient manner by companies worldwide, to achieve e.g. cheap access to supply-chain optimised and waste/pollution-management certified 3D printing. Another avenue worth exploiting is to use the well-honed supply chain of major chains, such as supermarket chains, to bring raw material into urban environments; and equally use their optimised waste-recollection system.
9) Data Craze:
a. Observation: Reference to big, open or private data appears in each powerpoint today. Three issues which I believe are important to bear in mind:
i. Big Data: There is no doubt that big data can give unique and unprecedented insights, mainly when cross correlated with data from different domains. However, we observed that most big data insights are very well known to those really working 24/7 in the concerned vertical. Big data is mostly used for spicing up the PPTs of the executives whilst not attending to the problems which could really be solved.
ii. Open Data: There is also no doubt that open data will be a major factor in making big data happen. To open data, however, cannot be enforced as those companies generating the data typically go through just-at-margin procurements – why would I release data on which somebody else will be capitalising on?
iii. Privacy Issues: The recent NSA scandal has not helped but building higher and stronger privacy walls is not the right way to go. Nature does not work like this; imagine the brain, based on privacy argumentation, refuses to instruct the arm muscles to retract after the temperature sensors in the hand signal burning heat? The real big data opportunities come with private data used carefully.
i. To make maximum usage of big data, you need to act on it. A simple working slogan, such as “Don’t sense without acting”, would immediately change the entire big data paradigm. Also, it is important to give access of large heterogeneous data sets to the right people, i.e. those who can actually act and use it advantageously.
ii. Open data will live its full potential once the value chain has been put in place where the business generating the data can be assured that part of the value generated from that data actually comes back.
iii. Intelligent or context-aware privacy mechanisms are needed to ensure that opportunities, both in making the world a more efficient but also more ethical place, are being made full use of.
a. Observation: We have become aware of the broken value chain between citizens and the decision makers within cities. There is a strong trend of re-engaging the citizen in the design process of making a city a smarter place. However, there is a danger of becoming too obsessed about this reengagement as i) by far not everybody wants to be involved in designing urban space (in fact, most of us just want to get on with life; the heated discussions among like-minded give us the impression that all want to be part of this process); and ii) even if you involve an eager crowd, your engagement will jump from 0.000001% to 0.0001% maybe – so no real improvement of involving the masses in redesigning the city.
b. Suggestion: Since people are by nature great in complaining, the process of delivering and acting upon these complaints ought to be made as efficient and transparent as possible. Simple feedback has always been the most effective way of improvement, and is an efficient way of involving the crowds.
I am keen on hearing your feedback; please, write to me under firstname.lastname@example.org or email@example.com, or tweet me at @mischadohler. I am equally keen on updating you on the smart city design challenges of 2014.