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SEPARATE: A tightly coupled, seamless IoT infrastructure for deploying AI algorithms in smart agriculture environments by Juan Morales-García; Andrés Bueno-Crespo; Raquel Martínez-España; Francisco J. García; Sergio Ros; Julio Fernández-Pedauyé; José M. Cecilia is a Computer Science article available to read on EtoBox.
What is SEPARATE: A tightly coupled, seamless IoT infrastructure for deploying AI algorithms in smart agriculture environments about?
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) obtains the best results in both prediction accuracy and computational time. On the other hand, an analysis has been carried out to determine how often the model must be retrained, obtaining results that in
Who reads SEPARATE: A tightly coupled, seamless IoT infrastructure for deploying AI algorithms in smart agriculture environments?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Juan Morales-García; Andrés Bueno-Crespo; Raquel Martínez-España; Francisco J. García; Sergio Ros; Julio Fernández-Pedauyé; José M. Cecilia
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Computer Science (Physical Sciences)