Resumen:
|
[EN] In recent decades, networked smart devices and cutting-edge technology have been exploited in many applications for the improvement of agriculture. The deployment of smart sensors and intelligent farming techniques ...[+]
[EN] In recent decades, networked smart devices and cutting-edge technology have been exploited in many applications for the improvement of agriculture. The deployment of smart sensors and intelligent farming techniques supports real-time information gathering for the agriculture sector and decreases the burden on farmers. Many solutions have been presented to automate the agriculture system using IoT networks; however, the identification of redundant data traffic is one of the most significant research problems. Additionally, farmers do not obtain the information they need in time, such as data on water pressure and soil conditions. Thus, these solutions consequently reduce the production rates and increase costs for farmers. Moreover, controlling all agricultural operations in a controlled manner should also be considered in developing intelligent solutions. Therefore, this study proposes a framework for a system that combines fog computing with smart farming and effectively controls network traffic. Firstly, the proposed framework efficiently monitors redundant information and avoids the inefficient use of communication bandwidth. It also controls the number of re-transmissions in the case of malicious actions and efficiently utilizes the network's resources. Second, a trustworthy chain is built between agricultural sensors by utilizing the fog nodes to address security issues and increase reliability by preventing malicious communication. Through extensive simulation-based experiments, the proposed framework revealed an improved performance for energy efficiency, security, and network connectivity in comparison to other related works.
[-]
|
Agradecimientos:
|
This work has been funded by the "Ministerio de Ciencia e Innovacion" through the Project PID2020-114467RR-C33 and by "Ministerio de Agricultura, Pesca y Alimentacion" through the "proyectos de innovacion de interes general ...[+]
This work has been funded by the "Ministerio de Ciencia e Innovacion" through the Project PID2020-114467RR-C33 and by "Ministerio de Agricultura, Pesca y Alimentacion" through the "proyectos de innovacion de interes general por grupos operativos de la Asociacion Europea para la Innovacion en materia de productividad y sostenibilidad agricolas (AEI-Agri)", project GO TECNOGAR. This work was supported by the research SEED project "Intelligent and trusted metaheuristic optimization model for agriculture using ubiquitous sensors network" Prince Sultan University, Riyadh Saudi Arabia, (SEED-CCIS-2022{109}) under Artificial Intelligence & Data Analytics Research Lab. CCIS.
[-]
|