Toward supporting food journaling using air quality data mining and a social robot

Gerina F.;Pes B.;Reforgiato Recupero D.;Riboni D.
2019-01-01

Abstract

Unhealthy diet is a leading cause of health issues. A powerful means for monitoring and improving nutrition is keeping a food diary. Unfortunately, frail people such as the elderly have a hard time filling food diaries on a continuous basis due to forgetfulness or physical issues. For this reason, in this paper we investigate the integration of nutrition monitoring in a robotic platform. A machine learning module detects cooking activities based on air quality sensor data. When cooking is detected, a social robot interacts with the user to fill the food diary through a conversational interface. We report our experience on the development of a partial prototype of our system. Moreover, we illustrate the results of preliminary experiments with annotated sensor data gathered over one month from a real-world apartment.
2019
Inglese
Ambient Intelligence. 15th European Conference, AmI 2019, Rome, Italy, November 13–15, 2019, Proceedings
978-3-030-34254-8
978-3-030-34255-5
Springer
11912
318
323
6
https://link.springer.com/chapter/10.1007/978-3-030-34255-5_22
15th European Conference on Ambient Intelligence, AmI 2019
Contributo
Esperti anonimi
2019
Roma, Italy
internazionale
scientifica
Context-aware computing; Healthcare; Social robots
no
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Gerina, F.; Pes, B.; Reforgiato Recupero, D.; Riboni, D.
273
4
4.1 Contributo in Atti di convegno
reserved
info:eu-repo/semantics/conferencePaper
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