31ºNorth together with the Urban Sustainability and Innovation Lab at the Porter School for Environmental Studies at Tel Aviv University launches a study, designed to simplify and unify the analysis of urban data, focusing on the specific resident needs. The idea is to create a universal typology of residents archetypes, or ‘city clusters’, developing an algorithm and measures for its definition using multiple data dimensions.
There is no single recipe for developing a smart city, moreover, there is not even a single definition of the term itself. Despite the external similarity of urban processes, each city is managed in different ways, functions differently, has different economic and technological conjuncture, etc. There are pros and cons in this: apparently, we wouldn't like all cities in the world to be the same, but such diversity in terms of local management and economic characteristics, unfortunately, makes city "smartening” more pricey and complicated, since it requires tailor-made methodological and technological solutions.
Today, the market of smart city technologies is estimated at about $40 billion, and it consists of hundreds of big and small, local and global players, providing services in all kinds of data-related areas: generation, collection, processing, storage, analysis, etc. The projects they implement, again, may seem quite similar, but each has its own specificity. For example, a lot of cities analyze traffic data, but in one case it can be public transport data owned by a city, in another – data of cellular operators, car hailing services, map developers, etc.; for its storage and processing can be used city's own resources or cloud services of big corporations, and methodology and conclusions can be determined by internal experts, international consultants, or scientists from a local university.
Let’s compare the two cities – big and techy Barcelona in Spain and small Messina in Sicily, Italy. The Smart City Barcelona program, first of all, is a top-down initiative. It covers 12 areas, including transportation, water, energy, waste, and open government. The technological platform is operated by such companies as Microsoft, Cisco, Accenture, Bismart, GDF Suez, and Cellnex. Sensors installed all over the city monitor all types of metrics, like noise, humidity, pollution and traffic congestion. Also, city actively promotes its open data project to motivate businesses to build their own apps. No wonder Barcelona’s Smart City program costs a fortune – only on waste management and recycling the city has spent about 1,5 billion euros over four years.
Totally different example is Messina, where a team of enthusiasts develops a service called SmartMe, that collects data from sensors installed in parking lots, on buildings, bus stops, and trash cans, and shares it online with several handy apps. All these sensors they had to install themselves – there weren't any legacy devices in the city to work around, and to do so the team launched a crowdfunding campaign two years ago, asking for about $17,200. Seeing the real value here, community supported the project, and SmartMe got more than twice the money. Now the team is partnering with other local tech companies, hoping to get a piece of the $15 million investment, promised by the city government.
The pain points of building smart cities
Both examples are indisputable success stories, although the reasons for such success are different: if in the case of Barcelona, a huge investment played a big role, then in the case of Messina, smart city technologies emerged thanks to the knowledge of a small group of enthusiasts. However, for many cities, both these parameters still remain significant limitations: American city managers admit that the two biggest barriers to the building of smart technologies in their cities are budget constraints and lack of expertise.
Finding the solution
Being aware of these difficulties, 31ºNorth together with the Urban Sustainability and Innovation Lab at the Porter School for Environmental Studies at Tel Aviv University launches a study, designed to simplify and unify the analysis of urban data, focusing on the specific resident needs. The idea is to create a universal typology of residents archetypes, or ‘city clusters’, developing an algorithm and measures for its definition using multiple data dimensions. To that end, the research team will first determine the fundamental city cluster analysis characteristics, and then will test the common elements of clusters between cities by applying the methodology to 5 selected cities around the world.
Identifying these generic clusters and challenges each group faces in everyday life, the first of its kind resident centric BI system can be developed. What will make it different from other tools? First of all, it can be useful for cities which don’t have enough budget and expertise for customised business solutions. Second, it’s a resident centric approach – using even standard socio-economic information about the city, the system will immediately visualize city residents and map their essential needs, and with more data from municipal sources it can be used to forecast and predict trends and behaviours.
Such a tool will allow cities around the worlds to immediately gain insights into resident challenges, understand the main pain points and use this information to define priority directions of smart city development, and therefore, plan the city budget more effectively.
The digital age drives cities to reconsider their old infrastructure centric approach, and pivot towards a new way of managing cities, driven by data. By providing a convenient methodology and solution for real-time management decisions based on actual resident needs, we hope to simplify the transition to a new technological level for many cities around the world.