Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) − a review

Fanuel, Ibrahim M.; Mushi, Allen; Kajunguri, Damian

doi:10.1051/smdo/2018001

Cited by 6 publications

(3 citation statements)

References 33 publications

(27 reference statements)

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“…Flood irrigation [17,22,25,27,28] Alternate wetting and drying (AWD) [22] Sprinkler irrigation [21,27,29,30] Drip irrigation [23,24,[31][32][33] Micro irrigation [14,34] Table 1. Cont.…”

Section: Various Irrigation Techniques Referencesmentioning

confidence: 99%

“…Low-pressure pipe irrigation [21,33,35] Channel lining [36,37] Furrow irrigation [28,35] Pivot irrigation [32] Das et al considered four key data fields, namely, the morphology of the plant, canopy, leaf area index, and fruit counts, using sensor suites containing a laser range scanner, multispectral cameras, a thermal imaging camera, and navigational sensors. Using the sensor suites, they were able to monitor the agriculture process effectively [26].…”

Section: Various Irrigation Techniques Referencesmentioning

confidence: 99%

See 1 more Smart Citation

Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture

Veerachamy

Ramalakshmi

Kavin

et al. 2022

Water

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The increase in population growth and demand is rapidly depleting natural resources. Irrigation plays a vital role in the productivity and growth of agriculture, consuming no less than 75% of fresh water utilization globally. Irrigation, being the largest consumer of water across the globe, needs refinements in its process, and because it is implemented by individuals (farmers), the use of water for irrigation is not effective. To enhance irrigation management, farmers need to keep track of information such as soil type, climatic conditions, available water resources, soil pH, soil nutrients, and soil moisture to make decisions that resolve or prevent agricultural complexity. Irrigation, a data-driven technology, requires the integration of emerging technologies and modern methodologies to provide solutions to the complex problems faced by agriculture. The paper is an overview of IoT-enabled modern technologies through which irrigation management can be elevated. This paper presents the evolution of irrigation and IoT, factors to be considered for effective irrigation, the need for effective irrigation optimization, and how dynamic irrigation optimization would help reduce water use. The paper also discusses the different IoT architecture and deployment models, sensors, and controllers used in the agriculture field, available cloud platforms for IoT, prominent tools or software used for irrigation scheduling and water need prediction, and machine learning and neural network models for irrigation. Convergence of the tools, technologies and approaches helps in the development of better irrigation management applications. Access to real-time data, such as weather, plant and soil data, must be enhanced for the development of effective irrigation management applications.

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“…Flood irrigation [17,22,25,27,28] Alternate wetting and drying (AWD) [22] Sprinkler irrigation [21,27,29,30] Drip irrigation [23,24,[31][32][33] Micro irrigation [14,34] Table 1. Cont.…”

Section: Various Irrigation Techniques Referencesmentioning

confidence: 99%

Section: Various Irrigation Techniques Referencesmentioning

confidence: 99%

Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture

Veerachamy

Ramalakshmi

Kavin

et al. 2022

Water

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show abstract

“…NSGA (Jarin et al, 2006) was also applied for the crop planning model to maximize total net bene t and minimize total cost. NSGA-II (Pal et al, 2009;Lalehzari et al, 2016;Sarker and Ray, 2009;Yusoff et al, 2011 andFanuel et al 2018) gains much popularity to solve multi-objective crop planning problems, water irrigation problems, etc. and in contrast to the strategy of single-objective optimization, NSGA-II optimizes every objective independently.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimal crop plan for optimum groundwater utilization considering profit maximization: A case study

Nath

Jain

Arora

et al. 2022

Preprint

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This paper presents a multi-objective optimization problem to identify an optimal crop plan by simultaneously maximizing profit and reducing groundwater utilization. An important economic and sustainable agricultural decision-making task is to make optimal use of resource constraints in a given planting period. To solve the problem, the NSGA II and NSGA III algorithms are used. The performance and effectiveness of both algorithms are examined by comparison of the results. In addition, the Pareto fronts are presented with graphical comparisons. The findings show that NSGA-III is a more viable tool than NSGA II to solve an optimal crop planning problem.

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A Systematic Review of Crop Planning Optimisation Under Climate Change

Randall,

Schiller,

Lewis

et al. 2024

Water Resour Manage

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Optimising the use of natural resources for food production in the context of changing climate is an increasingly important issue. Optimisation techniques have been shown to be remarkably effective for planning problems, and tools regional planners and farmers can use to determine the viability of agricultural land use planning into the future. This paper systematically reviews the recent literature in this area and draws out the key emerging themes: few studies to date have explicitly incorporated climate projections into optimisation models; increased tension for water resources between stakeholders; and various agricultural production systems of complex versions of crop planning. From this review it can be seen that increasing concentration on the use of climate projection models within agriculturally-oriented optimisation processes is a necessity.

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Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) − a review

Cited by 6 publications

References 33 publications

Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture

Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture

Multi-objective optimal crop plan for optimum groundwater utilization considering profit maximization: A case study

A Systematic Review of Crop Planning Optimisation Under Climate Change

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