A Soft Sensor to Estimate the Opening of Greenhouse Vents Based on an LSTM-RNN Neural Network
StadisticsView Usage Statistics
MetadataShow full item record
Author/sGuesbaya, Mounir; García Mañas, Francisco; Rodríguez Díaz, Francisco De Asís; Megherbi, Hassina
In greenhouses, sensors are needed to measure the variables of interest. They help farmers and allow automatic controllers to determine control actions to regulate the environmental conditions that favor crop growth. This paper focuses on the problem of the lack of monitoring and control systems in traditional Mediterranean greenhouses. In such greenhouses, most farmers manually operate the opening of the vents to regulate the temperature during the daytime. Therefore, the state of vent opening is not recorded because control systems are not usually installed due to economic reasons. The solution presented in this paper consists of developing a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) as a soft sensor to estimate vent opening using the measurements of different inside and outside greenhouse climate variables as input data. A dataset from a traditional greenhouse located in Almería (Spain) was used. The data were processed and analyzed to study the relationships betwee...
long short-term memory