Publications

Authors:

Castellini, A.; Farinelli, A.; Minuto, G.; Quaglia, D.; Secco, I.; Tinivella, F.

Title:

EXPO-AGRI: Smart Automatic Greenhouse Control

Year:

2017

Type of item:

Contributo in atti di convegno

Tipologia ANVUR:

Contributo in Atti di convegno

Language:

Inglese

Format:

A Stampa

Congresso:

BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE

Place:

Torino, Italy

Period:

19-21 October 2017

Publisher:

IEEE

ISBN:

978-1-5090-5803-7

Page numbers:

476-479

Keyword:

Logistic regression; Precision agriculture; Decision support system; Pest and disease forecast

Short description of contents:

Predicting and controlling plant behavior in con- trolled environments is a growing requirement in precision agri- culture. In this context sensor networks and artificial intelligence methods represent key aspects for optimizing the processes of data acquisition, mathematical modeling and decision making. In this paper we present a general architecture for automatic greenhouse control. In particular, we focus on a preliminary model for predicting the risk of new infections of downy mildew of basil (Peronospora belbahrii) on sweet basil. The architecture has three main elements of innovation: new kinds of sensors are used to extract information about the state of the plants, model predictors are generated from this information by non-trivial processing methods, and informative predictors are automatically selected using regularization techniques.

Product ID:

99457

Handle IRIS:

11562/970438

Last Modified:

April 29, 2023

Bibliographic citation:

Castellini, A.; Farinelli, A.; Minuto, G.; Quaglia, D.; Secco, I.; Tinivella, F., EXPO-AGRI: Smart Automatic Greenhouse Control  in Proc. of 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) , IEEE , Proceedings of "BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE" , Torino, Italy , 19-21 October 2017 , 2017 , pp. 476-479

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