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Numbers and Cognition in the Urban Environment

Overview

This workshop is structured on architecture, numbers and cognition with a primary focus on public space/traffic. Two broader topics pervade the workshop. One of them is more physical, involving translating the world into parameters, and the other is mapping social activities/feelings. The broad goal is to find connections between the two sets of topics. The environment around us consists of a number of physically countable and measurable parameters, which we can use to describe it (width of a carriageway, location of a cafe). Which parameters are best in describing or designing the world?

When, why and where are people moving and how long do they stop – this is an important set of topics, because the quality of space is largely dependent on the presence of people. The participants in the course will be challenged to find relationships between the physical world and human activity. It will be important to find a means and method for measuring and documenting the environment. Cognition referred to in the course name refers to experience that can be used in the future to make decisions to design and re-design space. Ideally, we envision the participants who complete the academy to be capable of imagining and perceiving the implications of 1,000 people or 100 cars passing a point.

The late 20th century brought a rise in computing power, which has resulted in a change in the accuracy and use of many calculations. In the past, it was not conceivable to calculate trajectories from one building to another manually, but now it is possible. Alongside this trend, a completely new field has arisen: various kinds of simulations. Simulations make it possible to model traffic, pedestrians or both at the same time. Gathering data has become more intensive with a focus moving from gathering qualitative data to collecting quantitative data. A large part of the summer school involves field observations, which helps instill intuition in participants as to what a given indicator means. This will also give them a clearer understanding of the computational processes and outcomes and they will be able to rationally assess the outcomes of some simulation or facts presented to them.

We are aiming to connect different aspects in an urban context. Some countable, measurable parameter and feeling or intuition, which should also be measurable. We will map the movements or activities of human masses, using photo and image analysis and Wi-Fi positioning to do so.

We urge you to keep ideas simple and trivial. It allows you to focus and go deeper. Every project should have two key features – a clear focus on what to measure and at least two different aspects that could be connected and compared. For example, traffic density and the safety of crossing the road. One could count cars and feeling to determine if they feel safe to cross the street at the same time. Comparing this kind of information could yield some surprising results. We will try to determine if traffic density could be used for predicting safety or whether it’s related more to the weather. How predictable it is? How different are the actions of different people? Could the same number of cars in a different location feel different? The focus is to look for some interesting connections and conclusions from the observations.

Participants will become well-versed in methods and means for quantitatively and qualitatively documenting the street-level space, which can in turn later be used for analysis of other places. The participant will also receive an overview of and access to software used in the framework of the workshop.

At the end of the summer school, all of the data that was gathered will be made public to allow third parties to use them in their projects – for example, to plan more fluid, safer traffic conditions.

LEARNING OUTCOMES. Participant:

• is well-versed in the methods and means for quantitatively and qualitatively documenting the street-level space, which can in turn later be used for the analysis of other places;
• has an overview of and access to software used in the workshop;
• has an understanding of collecting and processing data;
• has acquired basic knowledge in GIS, the functioning of Wi-Fi, machine learning and computer vision.

ASSESSMENT
The course ends with a public presentation of the results (pass-fail evaluation).

THE COURSE WILL BE TAUGHT BY:

Raul Kalvo, who holds an MA in architecture and urban planning from the Estonian Academy of Arts, is an architect and programmer, as well as a teaching staff member at the Estonian Academy of Arts. In the last four years, Raul has been engaged in building analytical models of cities and application of the models in various projects. Along with Mikk Meelak and Marti Kaljuve, he helped design the digital exhibits at the Estonian National Museum permanent exhibition entitled “Encounters”. He developed the concept for this workshop and led a similar workshop in 2017 and 2018 as part of Tallinn Summer Academy.

Mikk Meelak is an architect who is interested in meshing physical and digital space. He is the founder of Platvorm, a studio that develops concepts and builds innovative digital platforms with a focus on real-time data and dynamic user-generated content. He is the creator of the digital exhibits in the new permanent exhibitions at the Estonian National Museum and of the digital installations for Estonia’s EU Presidency, lead the research group of the Estonian Pavilion at the Venice Biennale of Architecture in 2014 and teaches creative coding at the Estonian Academy of Arts.

COST
Free

EKA Summer Academy of Art, Design and Architecture – Possible Futures” is supported by the European Regional Development Fund.

Programme structure

SCHEDULE

Monday, August 19. Introduction and group forming
9:00–10:30 Registration and intro. (Intro to Dataoverlay, Wi-Fi sniffing and machine vision)
10:30–12:00 Homework presentation and group forming
12:00–13:30 Lunch (on your own)
13:30–15:00 Working on hypothesis
15:00–17:00 Presenting hypothesis to tutors
17:00 Test data gathering

Tuesday, August 20. Learning tools and preparing surveys
9:00–10:30 Test data gathering (outside with your group)
10:30–12:00 Lecture on tools (GIS)
12:00–13:30 Lunch (on your own)
13:30–15:00 Lecture on statistical methods and data visualisation
15:00–17:00 Preparing survey

Wednesday, August 21. Data collection
9:00–12:00 Data gathering
12:00–13:30 Lunch (on your own)
13:30–15:00 Status update by one group member.
15:00–17:00 Data gathering
17:00–18:30 Optional. Technical lecture on how our tools work under the hood.

Thursday, August 22. Analysis and presentation
9:00–10:30 Lecture on tool and analytics and visualisation
10:30–12:00 Data gathering/Analysing data
12:00–13:30 Lunch (on your own)
13:30–15:00 Analysing data/Visualising
15:00–17:00 Presentation draft

Friday, August 23. Presentations
9:00–10:30 Each group representative presents using a projector.
10:30–12:00 Working on visualisation/presentation, tutors monitor
12:00–13:30 Lunch (on your own)
13:30–15:00 Wrapping up presentation
18:00–20:00 Public presentation (mandatory) and after-party

PLEASE CHOOSE CLUSTERS
We have prepared 5 clusters/topics for this year. These are a combination of methods and topics that you should expect to work with. The aim is to combine groups more effectively with a clear focus. When you register please choose option 1 and option 2. Also, write a short description on why you think this particular cluster suits you and what you expect to gain out of it. That helps us to prepare group participants together better.

Cluster descriptions:
Machine vision. You will learn how to extract pedestrian movement information by using machine vision. This cluster requires some technical knowledge. Most of the heavy calculation will be performed on site.
Wi-Fi tracking. You will learn how Wi-Fi tracking devices work and what the methods to analyse them are. You are tasked with examining larger scale and longer term (day) movements in urban context. This cluster suits those who would like to work with code and the more technical side of analytics.
How public amenities affect choice. You will be focusing on how public venues affect urban life. Or how life on the street affects revenue for venues. For example: Is there any relationship between people passing by and entering a cafe?
How traffic affects route choice. This cluster focused on combining two different types of traffic modes and focusing on how they affect each other. For example, when you feel safe crossing the street at a random location or how car traffic affects the route choice of a cyclist.
Social interactions. This is the most open cluster and you will be looking into social interaction on the street. In previous years there have been projects such as counting eye contact and studying how people interact when someone makes images. This is the most open-ended cluster.

Apply now! Summer semester 2019/20
Application period has ended
Studies commence
Jul 29, 2019

Application deadlines apply to citizens of: United States