Multispectral Cameras and Machine Learning Integrated into Portable Devices as Clay Prediction Technology

The present work proposed a low-cost portable device as an enabling technology for agriculture using multispectral imaging and machine learning in soil texture. Clay is an important factor for the verification and monitoring of soil use due to its fast reaction to chemical and surface changes. The s...

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Bibliographic Details
Published inJournal of sensor and actuator networks Vol. 10; no. 3; p. 40
Main Authors Helfer, Gilson Augusto, Barbosa, Jorge Luis Victória, Alves, Douglas, da Costa, Adilson Ben, Beko, Marko, Leithardt, Valderi Reis Quietinho
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2021
Subjects
Agriculture
Artificial intelligence
Clay
Clay soils
Color
Farms
Histograms
Image acquisition
Light
Light emitting diodes
Machine learning
multispectral image
Portable equipment
Productivity
Science
soil
Soil properties
Soil sciences
Soil testing
Spectrum analysis
Texture
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Summary:The present work proposed a low-cost portable device as an enabling technology for agriculture using multispectral imaging and machine learning in soil texture. Clay is an important factor for the verification and monitoring of soil use due to its fast reaction to chemical and surface changes. The system developed uses the analysis of reflectance in wavebands for clay prediction. The selection of each wavelength is performed through an LED lamp panel. A NoIR microcamera controlled by a Raspberry Pi device is employed to acquire the image and unfold it in RGB histograms. Results showed a good prediction performance with R2 of 0.96, RMSEC of 3.66% and RMSECV of 16.87%. The high portability allows the equipment to be used in a field providing strategic information related to soil sciences.
ISSN:2224-2708
2224-2708
DOI:10.3390/jsan10030040