Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC)

Quimbita-Zapata, Wilmer Enrique; Toapaxi, Edison; Llanos, Jacqueline

doi:10.3390/app12094235

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…survival in maize stubble and soil suppression [13]. Moreover, this monograph investigates the adoption and use of mobile internet technology in sustainable agriculture among wheat farmers [14], compression and heat generation by fungi in bulk maize with consideration of kernel cracking [15], and the implementation of a smart irrigation system with consideration of optimal energy management [16]. In addition, a method for extending the shelf life of apples after storage using low magnetic fields [17] and the theory of motion of a machine-tractor-trailer combination for harvesting beet tops [18] have been investigated.…”

Section: Contemporary Systems For Intelligent Farmingmentioning

confidence: 99%

Special Issue on the Engineering of Smart Agriculture

2023

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Section: Contemporary Systems For Intelligent Farmingmentioning

confidence: 99%

Special Issue on the Engineering of Smart Agriculture

2023

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“…where: δ p is the average density of the soil particles equal to 2.63 g.cm −3 and θ is the soil porosity in percentage. Finally, values of FC, PWP, δ b and the rooting depth (RD) are used to calculate the PSID using the equation [40]:…”

Section: Calculation Of the Pre-sowing Irrigation Depth (Psid)mentioning

confidence: 99%

Determination of Soil Physical Properties and Pre-Sowing Irrigation Depth from Electrical Resistivity, Moisture, and Salinity Measurements

Cordero-Vázquez,

Delgado-Rodríguez,

Cisneros-Almazán

et al. 2023

Land

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Seeds require adequate soil moisture prior to planting, and pre-sowing irrigation depth (PSID) represents the optimum seed moisture level. This work proposes a new methodology to obtain soil physical properties and PSID, that includes the application of the electromagnetic profiling method (EMP) as a fast and non-invasive technique. Soil electrical resistivity measurements obtained from an EMP survey are combined with soil moisture and salinity information as experimental input for the PetroWin program. The PetroWin program uses Ryjov’s theoretical model to determine fines content and porosity, and then, PSID values are determined. At the study site, variations in soil resistivity were controlled by variations in fines content and soil moisture, and not by variations in soil salinity. The rooting depth of the crops was limited by a soil thickness of 0.6 m. A PSID between 8 and 9 cm was determined for the site, resulting in a total water volume required of 5313 m3 to ensure that soil moisture reaches the field capacity. The proposed methodology constitutes an effective and efficient tool for the determination of the physical properties and irrigation parameters of agricultural soils and, consequently, for the sustainable use of irrigation water.

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“…The collected data are then analyzed and processed using sophisticated algorithms to determine the optimal amount and timing of water application. By considering factors such as weather conditions, crop requirements, and soil characteristics, smart irrigation systems can provide precise and targeted irrigation, minimizing water waste and maximizing crop yield [2,3].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Resource Allocation Algorithm for CR-WSN-Based Smart Irrigation System under Realistic Scenarios

Hassan

2023

Agriculture

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Cognitive radio wireless sensor networks (CR-WSNs) are a type of WSNs that use cognitive radio technology to enhance the spectrum utilization and energy efficiency. This paper proposes an energy-efficient resource allocation algorithm (EERAA) to prolong the lifetime of a WSN-based smart irrigation system under realistic scenarios. In the proposed algorithm, power allocation and subcarrier assignment are performed consecutively. Considering the impact of the intercarrier interference (ICI) caused by timing offset, the problem of maximizing network-averaged capacity is formulated considering power and interference constraints in realistic scenarios. The obtained results reveal that the proposed algorithm attempts to maximize the averaged capacity of the CR-WSN subject to the total power constraint and tolerable interference. Numerically, the proposed algorithm can reduce the network energy consumption by up to 30%, compared with conventional approaches, while maintaining a high level of system performance in terms of secondary users’ (SUs) averaged capacity.

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Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC)

Cited by 9 publications

References 21 publications

Special Issue on the Engineering of Smart Agriculture

Special Issue on the Engineering of Smart Agriculture

Determination of Soil Physical Properties and Pre-Sowing Irrigation Depth from Electrical Resistivity, Moisture, and Salinity Measurements

Energy-Efficient Resource Allocation Algorithm for CR-WSN-Based Smart Irrigation System under Realistic Scenarios

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