Journal
MEASUREMENT
Volume 164, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2020.108043
Keywords
Smart frost measurement in greenhouses; Anti-frost irrigation; Artificial Neural Network; Fuzzy expert system; Internet-of-things; Hybrid AI methods
Funding
- CONACYT Mexican mixed funds of the Zacatecas State Government (COZCyT) [ZAC-2009-C01-121774]
- Queretaro State Government (CONCYTEQ) [QRO-2005-C01-15218]
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A novel Agro-industrial IoT (AIIoT) technology and architecture for intelligent frost forecasting in greenhouses via hybrid Artificial Intelligence (AI), is reported. The Internet of Things (IoT) allows the objects interconnection on the physical world using sensors and actuators via the Internet. The smart system was designed and implemented through a climatological station equipped with Artificial Neural Networks (ANN) and a fuzzy associative memory (FAM) for ecological control of the anti-frost disaster irrigation. The ANN forecasts the inside temperature of the greenhouses and the fuzzy control predicts the cropland temperatures for the activation of five output levels of the water pump. The results were compared to a Fourier-statistical analysis of hourly data, showing that the ANN models provide a temperature prediction with effectiveness higher than 90%, as compared to monthly data model. Moreover, results of this process were validated through the determination of the coefficient of variance analysis method (R-2). (C) 2020 Elsevier Ltd. All rights reserved.
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