Yannic Lais

Risk of rockfall

The challenge presented required a thorough investigation of a road compromised by rockfall, as the pre-existing protective nets could no longer provide the expected level of safety.

Data on rockfalls from the past three months was used to determine the annual risk of fatalities caused by such incidents.

Depending on the outcomes of these calculations, the next step would either involve closing the road or allowing its use until the installation of new catchment nets was completed.

Smart Classroom

In this challenge, the task was to get data about air conditioning in a classroom with IoT sensors and advise the teacher to improve their air quality.

The data were collected with three feather esp32 and sent with BLE to a Raspberrypi zero, from the Raspberrypi the data was sent over an SSL Socket to a server, which sent the data to a relational database REST API.

Based on the analysis of the data we were able to provide valuable insights into the duration and number of times a classroom should be ventilated

Real estate calculator

In this challenge, Swiss real estate datasets were examined using various machine learning methods.

Models were developed to make predictions about the price or type of property based on different attributes. Individual models were further examined and compared with others.

Shared Mobility

The goal of this project was to understand the spatially differentiated demand for shared mobility services over time for Basel and Zurich.

First, an algorithm had to be developed to identify individual trips based on booking data. These trips were needed in the second step to quantify the influence of various factors using different models, i.e., which factors affect the demand for shared mobility services.

In the final step, based on the results, a spatial representation had to be created to show where shared mobility services could be useful.