The i-Log mobile application has been designed to collect data from the smartphone's internal sensors (details). The user is always informed of the data collection process thanks to a notification (details).
Periodically the user is asked to validate the sensor data by replying to very simple questions describing what he/she is doing (details). Questions can be answered immediatly or in a later moment but up to a certain time period.
All the data are collected in compliance with the EU Privacy laws. From a technical point of view, all the collected data are linked with a random unique identifier (details) that does not allow to link the data with the user who generated it.
The i-Log mobile application has been designed for Android devices. An iOS version is in development.
i-Log is very easy to use. The user can even not interact with the application at all. It starts when the phone boots and terminates when the battery is too low.
It is well known that using the phone to collect data is a battery intensive task. We designed the algorithms implemented in i-Log to be energy efficient and to affect the phone usability minimally, allowing to reach a full day battery life.
Our team starts to assemble to bring i-Log to sociological studies. So, a first idea of SmartUnitn is proposed
SmartKnowdive is first proposed to test the capabilities and robustness of i-Log.
SmartKnowdive starts and acts as a test bed for future projects. It makes us cut our teeth on 20 users and shows great promise!
The SmartUnitn first deployment starts with 72 students and will last for two weeks. Students provide us a huge amount of high quality data thanks to i-Log.
SmartUnitn is always searching for new people.
Full Professor - Unitn
Professor - Unitn