Abstract

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.

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