Abstract
In this paper, a comprehensive decision support tool based advanced monitoring system is developed to support transition to smart greenhouses for sustainable and clean food production. The decision framework aims to optimally control and manage the microclimate environments of smart connected greenhouses, where each greenhouse is defined as a self-water producing through an enhanced water desalination process. The main advantage of the current approach lies in the ability of the greenhouses to produce their water loads locally. This paper aims to develop an efficient decision tool able of performing specific monitoring and control functionalities to optimize the operation of the greenhouses where the aim is the energy and water savings. A decision model is implemented for the precise regulation and control of the indoor microclimate defining the optimal growth conditions for the crops. Furthermore, a predictive algorithm is developed to simulate in real time the operation of the greenhouses under various conditions, to assess the response of the system to storage dynamics and renewable sources, as well to control the complex indoor microclimate, energy and water flows, as well to optimize the crops growth. The developed tool is tested through a case study where the influences of climate data on the operation of the whole network are analyzed via numerical results.
Highlights
Transition from traditional to precision and smart agriculture has opened new challenges and perspectives regarding the development of efficient decision-making approaches and management tools where the main objective is the energy and water saving
While still limited applications have been initiated in the agriculture sector, even this sector has critical impacts and contribution in developing the economy, security and quality of life
This paper aims to fill this gap by suggesting a comprehensive and practical control framework based model predictive control (MPC) to optimally control the network of smart greenhouses
Summary
Transition from traditional to precision and smart agriculture has opened new challenges and perspectives regarding the development of efficient decision-making approaches and management tools where the main objective is the energy and water saving. Microgrid applications in the agriculture sector, may lead to overcome the challenges facing the transition to smart and precision agriculture as well as meeting the increasing number of regulations on quality, environment, and climate changes The adoption of this approach may enhance sustainable water and energy supply as well as optimal exploitation of the renewable energy sources. In this context, it is highly of interest to develop smart management solutions integrating artificial intelligence, advanced control techniques, metering and communication infrastructures and various technologies capable of accomplishing specific monitoring and control functionalities for smart greenhouses. This framework may foster the dissemination of high-quality research toward smart agriculture
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