SEPARATE: A tightly coupled, seamless IoT infrastructure for deploying AI algorithms in smart agriculture environments
Autor/es
Morales García, Juan; Bueno Crespo, Andrés; Martínez España, Raquel; García García, Francisco Jesús; Ros Amate, Sergio; [et al.]Fecha
2023-07-01Disciplina/s
Ingeniería, Industria y ConstrucciónMateria/s
Publish/Subscribe InfrastructureEdge Computing
Machine Learning
Deep Learning
Internet of Things
Smart Agriculture
Resumen
Precision agriculture generates large datasets from IoT infrastructures deployed for continuous crop monitoring. This data requires analysis to usefully transform this data deluge into insights that can deliver value-generating services to farmers in a timely manner. This paper introduces SEPARATE; a dynamic interoperable and decentralized infrastructure for executing both, training and inference stages of deep learning (DL) algorithms in smart agriculture scenarios. The presented infrastructure allows the execution of the inference stage at the edge, achieving a highly efficient and responsive local temperature prediction service to take actions based on the predictions generated. Moreover, the training stage is offloaded to the cloud along with the generated historical data, allowing the trained model to be periodically updated at the edge. On the one hand, our results show that the Convolutional Neural Network model together with the Long Short-Term Memory technique (CNNLSTM) obtain...