Nutrition plays a key role in both the prevention of several critical diseases and lead an healthier life in the modern society. In order to analyse household’s eating habits in the Italian scenario, authors propose the design of an innovative system called “Smart Shelve”. This system consists in a robotic structure integrable with various appliances, such as refrigerators, which allows to receive and deliver several types of foods in order to control their daily consumption. Smart Shelve is equipped with external optical sensors for food recognition, while inside it is composed of several food compartments in which load cells measure the weight of each type of food. The system is capable to warn the users who have recently conducted an incorrect style. The system is also able to send the acquired food consumption information to the cloud in order to provide statistical services regarding the nutrition style of clusters of users localized in a specific geographical area (e.g. district or region).

Preliminary Study of a Novel Shelving System for Nutrition Habits Measuring

FREDDI, ALESSANDRO;
2016-01-01

Abstract

Nutrition plays a key role in both the prevention of several critical diseases and lead an healthier life in the modern society. In order to analyse household’s eating habits in the Italian scenario, authors propose the design of an innovative system called “Smart Shelve”. This system consists in a robotic structure integrable with various appliances, such as refrigerators, which allows to receive and deliver several types of foods in order to control their daily consumption. Smart Shelve is equipped with external optical sensors for food recognition, while inside it is composed of several food compartments in which load cells measure the weight of each type of food. The system is capable to warn the users who have recently conducted an incorrect style. The system is also able to send the acquired food consumption information to the cloud in order to provide statistical services regarding the nutrition style of clusters of users localized in a specific geographical area (e.g. district or region).
2016
Inglese
Conti, Massimo; Madrid, Natividad Martínez; Seepold, Ralf; Orcioni, Simone
ser. Lecture Notes in Electrical Engineering, Mobile Networks forBiometric Data Analysis
392
41
50
10
978-3-319-39698-9
978-3-319-39700-9
http://link.springer.com/chapter/10.1007%2F978-3-319-39700-9_4
Springer International Publishing
Zurich
SVIZZERA
Esperti anonimi
Internazionale
no
2 Contributo in Volume::2.1 Contributo in volume (Capitolo o Saggio)
5
268
none
Freddi, Alessandro; Longhi, Sauro; Monteriù, Andrea; Ortenzi, Davide; Prist, Mariorosario
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11389/20396
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