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Get into detail and learn more about the motivation of our project as well as the aim in developing an open source activity tracker.
Get into detail and learn more about the motivation of our project as well as the aim in developing an open source activity tracker.
Unfortunately we have to inform you that the project “okinesio” is no longer actively maintained.
Every activity tracker on the market constantly records the users movements and stores data directly in the cloud. That‘s a big privacy issue!
Currently there is no activity tracker that doesn‘t push your data to servers in the US. If you have access to motion and sleeping data, you are able to keep track of daily routines or diseases. As a user, you don‘t know what happens with your sensitive data – direct access to your data is not given.
Some time ago big companies argued that smartphones aren‘t able to analyze complex motion data, so they have to store it in the cloud for further processing. With the latest generation of smartphones that have powerful processors, storage online isn‘t necessary anymore.
Cloud storage therefor aims for comfort, but it is not secure to synchronize data among your devices. It‘s used to retain the user and to sell the collected data.
We are a research team around Prof. Michael Zöllner at Hof University (Campus Münchberg) currently staffed by two research fellows in the disciplines Interaction Design and Information Design. Together with some students from the course Media Design we accomplish to develop the hardware and software in our research project.
As Designers we have the possibility to experiment with Processing and Arduino to create remarkable interactive projects and gain a lot experience with these practices. We also use open source and web technologies like HTML5 or Javascript.
We are developing a module (to be more specific: an activity tracker), that takes privacy seriously and let the user regain control over his sensitive data. Besides that we build on open hardware (Arduino) and open software to enable creative minds to be part of the process and further to act as a basis for their own projects or modifications.
There’s an app for our module that will provide the possibility to analyse, compare and visualise generated motion data. The recorded data is transferred directly to the mobile device and is stored there locally. Analysis and visualisations exclusively take place on the device itself.
Our aim is to create a platform for motion analysis and to inspire the digital community to contribute new ideas to both, hardware and software.