Results on spatio-temporal estimation of temperature and soil moisture in La Colmena (Paraguay)

被引：2

作者：

Manzano, J. M. ^{[1
]}

Orihuela, Luis ^{[1
]}

Pacheco, Erid ^{[2
]}

Pereira, Mario ^{[1
]}

机构：

[1] Univ Loyola Andalucia, Avda Univ S-N, Dos Hermanas 41704, Spain

[2] Alter Vida, Itapua 1372, Asuncion, Paraguay

来源：

IFAC PAPERSONLINE | 2022年 / 55卷 / 32期

关键词：

Monitoring of spatially distributed systems; Data-based estimation; Internet of things; Sensors in agriculture; AI in agriculture;

D O I：

10.1016/j.ifacol.2022.11.150

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents results on spatio-temporal estimation of agricultural soil variables using a novel methodology, called kinky inference. The methodology is applied to the temperature and soil moisture estimation in a bell pepper (Capsicum annuum) crop in La Colmena, Paraguay. Data is collected with in-situ devices equipped with sensors and endowed with communication capabilities to send the information to the cloud. The proposed methodology is able to learn from the received data, and produces reliable estimations for any spatial and temporal locations. Copyright (C) 2022 The Authors.

引用

页码：265 / 270

页数：6

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