Work

Soil digitalization using LED sensors

Year: 2026

Type: article

Abstract: In this paper, we propose a method of data collection from different sensors through a software developed by Sensichips s.r.l., SLM-Studio, which can then be compared with MLP machine learning models trained through data available on the Sensichips website. The measurements performed by the multispectral SpeCtroscoPe SCP can be applied in different fields of precision agriculture ranging from irrigation water monitoring to the health status of plants and soils up to the monitoring of the chemical-physical conditions of the air.

Source: Measurement Digitalization

DOI: 10.1016/j.meadig.2026.100033

Authors: Federico Fina, Massimo Piotto, Simone Contardi, Fabio Leccese

Institutions: Roma Tre University, University of Pisa

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $2,100