首页|Applications of new technologies for monitoring and predicting grains quality stored: Sensors, Internet of Things, and Artificial Intelligence

Applications of new technologies for monitoring and predicting grains quality stored: Sensors, Internet of Things, and Artificial Intelligence

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  • NSTL
  • Elsevier
The objective of this review was to evaluate current studies that addressed the use of sensors in stored grains, Intenet of Things (IoT) precepts and Machine Learning (ML) technologies in post-harvest to identify resources and new possibilities for technological development that can help in the monitoring the quality of stored grains. The review results demonstrated the wide application of sensors and devices to gather information in real-time based on the basic principles of good grain management and computational data analysis tools. It was verified that the results collected in real-time enable better decision-making in situations where there is a risk of loss and deterioration of stored grain due to variationsin factors like water content, grain mass temperature and relative humidity intergranular air. Thus, the quality of stored grain can be predicted by the equilibrium moisture content and CO2 concentration monitoring in the intergranular air.

Carbon dioxideControl systemsGrain lossesMoisture grainPost-harvest operationsDRY-MATTER LOSSESCARBON-DIOXIDESTORAGE ENVIRONMENTHERMETIC STORAGENEURAL-NETWORKSILO BAGSCALLOSOBRUCHUS-MACULATUSMOISTURE MEASUREMENTPOPULATION-DENSITYRELATIVE-HUMIDITY

Lutz, Everton、Coradi, Paulo Carteri

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Univ Fed Santa Maria

2022

10.1016/j.measurement.2021.110609

Measurement

Measurement

SCI
ISSN：0263-2241
年,卷(期)：2022.188
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