Why did you decide to conduct such a study?

This is actually the starting point of a bigger study of the Petrogradsky District that we’ll be conducting over the next few months. This project will be conducted by first year Master’s students following the institute’s Urban Development and Urban Informatics programs; having gotten the theoretical knowledge during their previous semester, they’ll be now applying it to practice.

Part of this study will be dedicated to analyzing the situation in winter, as every season comes with its peculiarities. So, we assessed the quality of winter cleaning using a ten-to-one scale, where “zero” corresponds to a complete disaster and “ten” reflects an ideal situation. We paid attention to such things as the condition of pavement, sideways and road surfaces, presence of icicles and ice dams on buildings’ gutters, or snow piles hindering passage. We also studied sites of winter activities, both official ones like skating and hockey rinks and the unofficial ones like self made chutes.

Petrogradsky District
Petrogradsky District

On the whole, the complex study we’ll be conducting implies gathering a huge amount of all kinds of data, including data from information systems. We’ll present our results at the St. Petersburg International Economic Forum and the International Spatial Development Forum. We will also use this data for developing a system for modeling pedestrian routes in the Petrogradsky District which we plan to present at ICON-LA (International Conference On Landscape Architecture: Towards sustainable urban environments) in June 2018.

At the current stage, you already have interesting results - you’ve developed an interactive map of the quality of cleaning. How do you plan to use this data?

As I’ve already told you, field observations when students visit almost every street, park and square, photograph and map them is only a part of the study which has to do with the quality of cleaning.

In the near future, we plan to conduct a series of hackathons where we’ll be using the data from the Committee for City Improvement and Roads’ webportal. We expect that it’s possible to use automation methods to get data on service vehicles’ routes, and add it to our analysis.

This may help us find the correlations that will highlight the downsides of the current organization of service vehicle’s work. In future, such data can become the groundwork for improving it. Though our assessment is subjective, it reflects the citizens’ perception and can be used by the city’s administration to manage the problem areas better.

How actively do governmental agencies use the results of such studies?

The Institute of Design & Urban Studies has long been cooperating with governmental agencies and district administrations. Back at the last Spatial Development Forum we showed a preliminary model of how urban data can be presented, on the example of the Petrogradsky District. We actively collaborate with several of the city administration’s committees that understand that informational technologies are the future. We will use the data that we gathered during the recent project to create a report that can be useful to the city’s officials, and send it to the Petrogradsky District administration.

You plan to present the results of your project at the St. Petersburg International Economic Forum that will take place in June. How will you organize the work on the project in the following months?

I expect that we’ll be using tens of different sets of data for our research, and our students have already started to look for them. Within a month, we’ll decide on the final list of sources, and start thinking of ways to get the necessary data from them. The problem here is that in some cases, we get ready-for-use data, csv-files, for instance; but oftentimes, we have to deal with a vast amount of information represented as texts on websites or even scans of documents. Still, that is an interesting research task, as well - to develop algorithms that will automatically derive data even from such sources. I believe that we’ll spend about a month and a half on these issues.

Steve Kuddins
Steve Kuddins

Later in spring, around April, when the weather becomes better, we’ll continue with the field observations in order to find out which data we lack after gathering it from all the possible information systems and other sources. We’ll gather the remaining data, and verify the data we already have.

Eventually, we want to create the most accurate database on all objects - buildings, landmarks, cultural sites, venues and such. We will also study all public spaces, specify the properties of streets, alleyways, avenues, embankments, sideways, squares and parks.

What is all this for? In future, all this data will allow us to create digital models, including predictive models of the district’s development. This will be yet another task for the students of ITMO’s Institute of Design & Urban Studies: they will solve the task that will help understand how vast amounts of data can be used to make hypotheses and understand what and where can we improve.

What kind of improvements can these be?

These improvements can be both local, like rearranging some small part of a street or some crossroads, so that they become more safe and comfortable, and strategic, like renovating whole territories of the so-called “grey zones”. For instance, we have the Petrovsky island overbuilt with industrial buildings and warehouses. It is only natural that we will have to redevelop this territory in the future.

Street cleaning in St.Petersburg
Street cleaning in St.Petersburg

Cities all over the world are already demonstrating the benefits of this approach. For instance, the beautiful beaches of Barcelona were once industrial areas; just 30 years ago, vessels unloaded oil there. The situation was similar to what we have now in St. Petersburg, as our citizens have to go to nearby towns like Zelenogorsk to access the coastline. In Barcelona, the city administration made the decision to relocate the industrial objects, and the current state of the city proves this decision right.

Speaking of information technologies and mathematical models, how do the methods and approaches that we use in Russia differ from those adopted in other countries?

With regard to providing for the urban infrastructure and overall comfort, we still fall behind in many areas, especially when it comes to transport, but we are definitely at the forefront of everything that has to do with information technologies and their application in the development of the smart city concept. For instance, this year we expect to publish several important articles in international-level journals. These articles will be dedicated to topics that still haven’t been properly researched by our foreign colleagues, who have great expertise in making decisions based on experience and practice, but not in creating and using mathematical modeling for the purposes of urban development.

Last autumn, I followed a distance education course by ETH Zurich dedicated to the concept of responsive cities. What was it about? While the smart city concept implies that we have many technologies, know what the citizens need, and give it to them, responsive cities are the next step when we provide solutions on the citizens’ request. In other words, we first ask their opinion, and not just make decisions on their behalf.

Point is, when I applied for the course, I thought “well, I’ll complete it and it’ll open my eyes to how it’s really done”. But I soon understood that for the most part, we are already doing it right. By no means are we falling behind in what has to do with information technology. And now our task is to develop our best practices and apply the experience we already have.