Duration: from 5 hours(incl. lunch break.)

Contents: methods from the field of AI (machine learning), metrics, acceleration
Previous knowledge: Euclidean distance (3D), vectors, magnitude of a vector
Participants: Mathematics courses from grade 11
Created by: Katja Hoeffer, Sarah Schönbrodt
Registration: Dates can be arranged individually using this form.

Mobile devices, such as smartphones, have become constant companions in our everyday lives. Around 3.6 billion people worldwide use a smartphone. In addition, interest in evaluating people's habits and daily routines has increased in recent years. This includes, among other things, the analysis of the activities performed. With the tremendous advancement of sensors in smartphones, they can be used to detect human activities. But how does activity recognition work and what does it have to do with math?

In this workshop, students:will work with real activity data and develop their own mathematical model for activity recognition. In doing so, they use current methods from the field of artificial intelligence.

Image source: https://br.atsit.in/de/wp-content/uploads/2021/05/so-sehen-sie-in-der-fitness-app-fur-das-iphone.jpg

The following mathematical contents are required as prior knowledge for the processing of the learning material:

• Euclidean distance between two points (3D)
• vectors
• magnitude of a vector

All other mathematical contents are introduced in the learning material in a problem-oriented way.

Page in progress

In the downloadable zip folder below you will find all presentations, worksheets with solutions and the lesson plan for this workshop. The zip folder is password protected. We will gladly send you the password by mail upon request.

Download

• Hoeffer, K.: Aktivitätserkennung auf dem Smartphone - Entwicklung von Unterrichtsmaterial für computergestützte mathematische Modellierungsprojekte, Master's thesis, KIT.