MANZANO CRESPO, JOSÉ MARÍA, ORIHUELA ESPINA, DIEGO LUIS, Pacheco, Erid , PEREIRA MARTÍN, MARIO

No

IFAC-PapersOnLine

Proceedings Paper

Científica

✗

✗

0.354

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144818799&doi=10.1016%2fj.ifacol.2022.11.150&partnerID=40&md5=76e146e588746f32fec44c164582d238

22/11/2022

000889052400046

2-s2.0-85144818799

10.1016/j.ifacol.2022.11.150

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.

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

• JOSÉ MARÍA MANZANO CRESPO
• MARIO PEREIRA MARTÍN