The i-Log system

Smartphone Sensors

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).

User Feedback

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.

Privacy Aware

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.

Android Devices

The i-Log mobile application has been designed for Android devices. An iOS version is in development.

Easy to use

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.

Battery Efficient

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.


The list of sub-projects of Smartrams.

SMART Knowdive

Internal Knowdive group experiment


Involving bachelor students from Unitn


Involving the municipality of Trento


What is the story so far

  • October 2015

    Great minds think alike

    Our team starts to assemble to bring i-Log to sociological studies. So, a first idea of SmartUnitn is proposed

  • March 2015

    SmartKnowdive is first proposed to test the capabilities and robustness of i-Log.

  • October 2016


    SmartKnowdive starts and acts as a test bed for future projects. It makes us cut our teeth on 20 users and shows great promise!

  • November - December 2016

    Moving to SmartUnitn

    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.

  • December 2017

    SmartTN comes to life

    SmartTN will begin its first deployment in the municipality of Trento, involving up to 10.000 citizens.

Our Team

You need smart people for a smart project

Fausto Giunchiglia

Full Professor @ Unitn

Andrea Passerini

Associate Professor @ Unitn

Mattia Zeni

Ph. D. Student @ Unitn
(Technology Architect)

Enrico Bignotti

Ph. D. Student @ Unitn

Ivano Bison

Associate Professor @ Unitn

Elisa Gobbi

Phd student in Sociology @ Unitn

Ivan Kayongo

Master Student @ Unitn

Liviu Bogdan

Master Student @ Unitn

Gabor Bella

Postdoc @ UNITN

Paolo Poppi

Municipality of Trento


  • [1]  F. Giunchiglia, E. Bignotti, and M. Zeni, "Personal context modelling and annotation," To appear in Pervasive Computing and Communications Workshops (PERCOM Workshops), 2017 IEEE International Conference on , 2017. (Download)

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