Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensor Network and Machine Learning

04/26/2022
by   Cecilia Occhiuzzi, et al.
4

Accelerated ripening through the exposure of fruits to controlled environmental conditions and gases is nowadays one of the most assessed food technologies, especially for climacteric and exotic products. However, a fine granularity control of the process and consequently of the quality of the goods is still missing, so the management of the ripening rooms is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a non-destructive RFID-based system for the automatic evaluation of the live ripening of avocados. The system, coupled with a properly trained automatic classification algorithm based on Support Vector Machines (SVMs), can discriminate the stage of ripening with an accuracy greater than 85

READ FULL TEXT

page 1

page 3

page 4

page 5

page 8

research
07/08/2019

Development of email classifier in Brazilian Portuguese using feature selection for automatic response

Automatic email categorization is an important application of text class...
research
01/05/2021

Support Vector Machine and YOLO for a Mobile Food Grading System

Food quality and safety are of great concern to society since it is an e...
research
10/12/2016

Exploring the Entire Regularization Path for the Asymmetric Cost Linear Support Vector Machine

We propose an algorithm for exploring the entire regularization path of ...
research
07/05/2016

An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning

We propose a clustering-based iterative algorithm to solve certain optim...
research
05/13/2022

Fault Detection for Non-Condensing Boilers using Simulated Building Automation System Sensor Data

Building performance has been shown to degrade significantly after commi...

Please sign up or login with your details

Forgot password? Click here to reset