Archive for July, 2019

With a population of over 12.6 million people, Moscow is considered the second densely populated city in Europe (after Istanbul). Living in a city like this becomes a real struggle both for its inhabitants and city planners. One of the most crucial aspects, which makes a city comfortable for living, is its transportation system. Even though Moscow metro is one of the longest in the world and has a daily ridership of around 7 million people, its capacity is still insufficient for the Russian capital. However, there is a new mean of public transport which develops really dynamically – bike-sharing.

Bike-sharing was introduced to the streets of Moscow in 2015. It is a special service provided by Velobike and Moscow Transport Department which allows the users to take a bicycle from one dock-station and return at another for a fee. Docks are special bike racks that lock the bike, and only release it by computer control. The user enters payment information, and the computer unlocks a bike. The user returns the bike by placing it in the dock, which locks it in place.

Since 2013 Velobike showed outstanding statistics: the number of bikes rose from 500 to 4300, the number of stations increased from 79 to 430, and the number of rides per a season – from 70,000 to 4.25 mln.

However, bikes still remain comparatively unpopular. For instance, car sharing in 2018 was used over 6 million times in 6 months of 2018. Even though bikes are cheaper, more environmentally friendly, and do not have traffic jams in Moscow, people tend to use cars more often.

Moreover, cycling infrastructure still leaves much to be desired. The improvement of customer experience by expanding the bike lane coverage would encourage locals and visitors to use the bike-sharing services more extensively.

Therefore, the analysis of Moscow bike-sharing could help to estimate the current trends in cycling in Moscow and develop the strategy for improving this service in the Russian capital.

Class: Technology & City Project.

Material: Plywood, acryl, Arduino, RFID scanner, motors.

Aim: Create the prototype for the automatic waste separation tube.

DataTube is an improvement of the existing waste tube in Russian houses with an aim to make recycling easier to local people, to encourage recycling behaviour, collect data about waste production for the researchers and introduce recycling programs for buildings depending on their waste production. The project was inspired by existing social and digital studies. For example, a study by Sterner (1998) showed that if recycling takes more time, people less willing to recycle and tend to produce more waste. Another work which was an inspiration is TrashTrack where tracking technologies were used to understand the movement of waste after its disposal. For DataTube project waste play a role as an indicator and social profile of the person who throws it away. From waste activities, different personal information can be understood: social statuses, gender, age, hobbies and etc.

DataTube prototype is based on Arduino Leonardo with RFID scanner (code reader), servo motors and IR sensors. The mechanism is consisting of “trash stoppers” (Separator 1) controlled by servo motors and then Separator 2 which are also controlled by servo motors. By default, Separator 1 is always in a closed position to prevent garbage to fell directly to the bins without separation. If the code reader will be not able to recognise RFID then waste will go to the general waste bin. In the future trash bins can be equipped with sensors which identify fullness of the bin and automatically send a request to the Management Company to take appropriate actions . Also, the number of recycling bins will be more then three.

The first real prototype of DataTube.
The schematic representation of the DataTube and first real prototype.

The Arduino code for the separators and motors can be found via the QR code below. Or via the link

DataTube is an example of what the future waste tube can be to provide convenient waste separation to the Russian householders. Their easier solution exists, for example recycling containers, but our goal was to change architecture with minimum impact on human behaviour. The major limitation of the project as there no studies available about people’s behaviour towards waste tube: some houses remove them; others prefer to not use waste tubes due to the unsanitary conditions. Before implanting such program additional research is needed.


Sterner, T. & Bartelings, H. (1998). Household Waste Management in a Swedish Municipality: Determinants of Waste Disposal, Recycling and Composting. Environmental and Resource Economics, pp.
473 491. [Online]. Available from:
Date accessed: 11 July 2019

TrashTrack (n.d ). [Online]. Available from:
Date accessed: 11 July 2019

ATTENTION: PHOTOS OF THE PROJECT WILL BE ADDED LATER DUE TO absence of laptop with all the working materials on all the projects

Class: Technology.

Software: Autocad, Rhino.

Material: Styrofoam 150*150*60 mm.

Task: Create the figure by using plywood ( or Styrofoam in my case) which is possible to cut with CNC machine.

Drawing the project

Our first task in the 2nd semester in Shukhov Lab was to create a 3-D object in cad software in order to cut it out on the CNC-machine afterwards.

After taking some time to find an interesting project I assumed it would be nice to take something big in real life and to scale it down as a CNC-project. Thus, my working on the mini-golf field started.

I was inspired by the photo of golf-club, located in Rostov region called Golf Country Club “DON”

‘place for photo’

I started to work in Autocad, proceeding later in Rhino software. The problem was to make the surface smooth without using Metaballs plugin. After several hours of ideas and the same amount of time for creation I managed to get something looking like that:

‘place for photo’

Actually, the edges appear to be not that smooth as I planned them to be, but still it looks original and worth trying to cut the golf field out. We decided with the tutor Ivan it would be better to try this project on the styrofoam form not to spoil the wooden sample just in case.

‘place for photo’

Cutting time

The process of cutting appeared to be something interesting because it was unusual to me to visualize the accurate work on tiny object by the big machine, capable to cut almost anything from the piece of square. It is important to fix the sample of material in order not to allow it change its position while the special drill head does its work.

The result

After approximately 25 min we managed to get the result of the whole concept looking this way:

‘place for photo’

I guess, from the wooden sample it would look much nicer, but we get what we get, next time maybe we’ll try something more worth to spoil the real wooden sample:)

With this project I got the idea how to cut out any 3-D object you want to transfer it from the virtual reality to real life.

Who: Danil, Ali.

Materials: Plywood 300*300*4mm( for Khruschevka prototype), Arduino, Light sensor, sunlight battery, LEDs, wires, resistors.

Class: City project

Software: Autocad, Rhino 6.0, Arduino IDE

Task: To think about the Khruchevka problems, make a research of the problem and find the possible solution

After long hours of arguing and searching for the real problem about Moscow typical 5-storey K-7 type building we found out, that thys time of amenity lack the lighting outside the building and requires some changes about it.

After long process of investigating the light topic we decided to make the project of light which would make Khruschevka brighter, smarter, safer and more self-sufficient.

We decided it would be good to make the whole building structure on the laser cutting machine and also to lasercut one more prototype of bigger scale in order to make it more visible and bigger to integrate that electronic stuff.

So, as former engineer students we prefer with Ali traditional Autocad software and drew there the building facade, which looked like this:

Here you can see some elements of the semi-final prototype, we forgot to take the photos dering the laser-cutting time(

While Ali was connecting the parts of the building to make it one piece I was working on the arduino and the electronic part to make the system get the electricity from the light via the sun battery and turn on the building light as soon as it gets darker.

While Ali was connecting the parts of the building to make it one piece I was working on the arduino and the electronic part to make the system get the electricity from the light via the sun battery and turn on the building light as soon as it gets darker.

A light sensor and a battery in composition.

Unfortunately, when writing this blog I left the final presentation on my study laptop. but here you can see the scheme, which primitively explains the idea (ooops, it seems liek there is no LEDs here on the scheme, but its clear that the system needs to supply something with electricity)

The first steps on coding the arduino :

Actually, I left original code on the laptop also, so I put here the sample – the code, from which I started to work as a start-point

We also add an option that the light would change its colour according to the state of light: the darker it gets, the more number of light you can see. We had an idea to create some king of the light watch, when the children, playing on the playground, would understand the approximate time by the que of colors the house lighting gives. Maybe a better option would be to connect the light with the digital clock itself to increase the accuracy of the system.

Below you can see the look of our prototype:

So, this is what we came to finally…. for us it was quite struggling to make even this kind of not very complex project on our won on some days, but we were happy to finish everything on time. Actually, our project was more about the research, so we hope during the next semester we will present something more unique and technically inspiring:)

By Coffee Team: Semen, Daniil & Maxim

How much consumers benefit from restaurant chains, what are the advantages of visiting a chain restaurant in comparison with non-chain? If it concerns low price category, that is fast food or Quick&Casual, the network is favorable and convenient to the consumer. Moreover, it can be a major incentive for consumption. This is especially noticeable on the food courts – the most visited are network institutions. As for the chain of restaurants of elite and middle category, it should be noticed that people do not go to the network, they GO TO the RESTAURANT. There are few people who go only to one network cafes, neglecting all the rest for fundamental reasons. As a rule, it is different: the network like only one or two, well, three restaurants.

Restaurant chains are increasing the geography of presence, but the market is still far from saturation. About 70% of the country’s fast food establishments account for 12% of the population living in Moscow. Here’s a table with the number of cafes-restaurants in some russian cities, but our experimental one is the first.

In nowadays Moscow there are 11,000 food service facilities. Approximately 41% of them (4,500) are good quality restaurants and cafes — with a certain format, clear concept and structure.

To know for a fact, 26 % of the restaurant market is consolidated by the largest players — holdings and top chains.

The structure of the restaurant market of Moscow
45 % — network food facilities;
27 % — non-network food facilities;
28 % — restaurants and cafes without format, which can and Shawarma sell, and wedding play. They do not fall under the concept of a quality operator.

After these kind of statistics let’s talk about our task & final project. What we wanted to do was to make a research on the cafe market and as a result recieve the information how the cafe location depends on such factors, as The idea was to do the following:

  1. Count the number of network & non-network cafes & restaurants around Moscow.
  2. Find the proportion between these two types of facilities.
  3. Find the correlation between #2 and 1sq m cost in Moscow districts. This will help us to understand how the rent price affects the location and density of cafes.
  4. Find the correlation between #2 and population to find the dependence between Muscovite concentration and cafes location.

Working process

In order to collect all the data and make a research we had to use the following software:

….. and others like google.maps

Overpass-turbo occured to be very helpful software, where you can sort & filter by any kind of amenity, download the data and use it in other programs. But, please, remember, that it works in Russia with vpn only.

Net & non-net cafes correlation

First, we submitted the location of net & non-net cafes & restaurants and found out their correlation. You can see the results below

The density of network cafes: the brighter the color of the district – the less the density of the cafes in this district is

The correlation of non-net & net cafes:

We divided non-net by net cafes. The brighter the district is – the smoother the correlation is.

As you can see, it turned out that the closer you are to the city center the less is the proportion. Though it may seem logically at first that it should be more network cafes in the centre, but we think that the reason could be because of the fact, that network cafes usually require more sq m for the spot and the rent price in the centre is too high to rent big facility. Non-network can rent a small facility, because quite often they don’t need much space. As a prove of our idea here is the cost heat map of Moscow.

Proportion vs sq/m cost

The next thing we worked on was to find the relation between two cafe types and population in Moscow districts.

Proportion sq m cost

On the left side you can see the population density while on the right sq m cost in Moscow correspondingly. As for the cost, it was quite obvious to get this kind of graph. The most highly populated areas occured to be the North-East region & South-East due to their regarding low quadrature price because of several factors: much industry, less infrastructure, worse ecology.

Proportion vs population

Cafes proportion
Moscow population
Proportion Population density

Now we compared the same cafe-proportion graph with the graph of the population of Moscow by districts and discovered that the the proportion number non-net/net cafes increases in the areas with lower population. But here we must say that we took into account the population as a living place factor. Which means if we consider the man’s work place and other during-day factors the situation will change. That means that net-cafes tend to open in districts with dense living population whereas non-net ones bet not on the population but on other factors.

To add more info to our research we united the two parameters: cafes & population. The graph to the kind of form, which tells, that the highest concentration of both occurs to be in the North-Western part of Moscow.


So, what did we get from this research?

  1. Found the balance/disbalance between net/non-net cafes
  2. Found out how the price for the real estate influences the spread of cafes
  3. Found the graphical connection between the number of people, living in the districts, and the predominance of each type of cafes.

The last, but not the least, is that we learnt, how to get the necessary data about the city by using special map-engine software. So, the next time we have to make a research and in case we need some information about any city in the world, we know how to make it and make it effective and fast.



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