What is it about?

The Frost represents a serious technological challenge if the crop sustainability is to be ensured. Thermal comfort in greenhouses is a key fact to enhance productivity, due to the excess demand of energy for heating, ventilation and agroclimatic conditioning.

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Why is it important?

A artificial neural network (ANN), trained by a backpropagation algorithm was designed and implemented for the smart frost control in greenhouses in the central region of Mexico, with the outside air temperature, outside air relative humidity, wind speed, global solar radiation flux, and inside air relative humidity as the input variables.

Perspectives

The results with IA method showed a 95% confidence temperature prediction, with a coefficient of determination of 0.9549 and 0.9590, for summer and winter, respectively.

Dr. Alejandro Castañeda-Miranda
Creativity and Innovation Center 4.0 (CIC 4.0), Technological University of Queretaro (UTEQ)

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This page is a summary of: Smart frost control in greenhouses by neural networks models, Computers and Electronics in Agriculture, May 2017, Elsevier, DOI: 10.1016/j.compag.2017.03.024.
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