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Design Example: Design of an Irrigation Channel01:27

Design Example: Design of an Irrigation Channel

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Trapezoidal channels are widely used in irrigation systems due to their cost-effectiveness and efficiency in conveying water. Trapezoidal channels feature a flat bottom and sloping sides, making them stable and easier to construct compared to other shapes. The bottom width and side slope ratio are determined based on the required flow capacity and site conditions. The side slope is kept gentle for unlined channels to prevent soil erosion.Hydraulic parameters in channel design include the flow...
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Though evaporation from plant leaves drives transpiration, it also results in loss of water. Because water is critical for photosynthetic reactions and other cellular processes, evolutionary pressures on plants in different environments have driven the acquisition of adaptations that reduce water loss.
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Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
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PI Controller: Design01:24

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Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
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Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
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Related Experiment Video

Updated: Jan 10, 2026

Author Spotlight: Unraveling the Role of Earthworms in Enhancing Mineral Weathering for CO2 Removal
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Edge-Computing Smart Irrigation Controller Using LoRaWAN and LSTM for Predictive Controlled Deficit Irrigation.

Carlos Cambra Baseca1, Rogério Dionísio2,3, Fernando Ribeiro2,3

  • 1Grupo de Inteligencia Computacional Aplicada (GICAP), Departamento de Digitalizacion, Escuela Politecnica Superior, Universidad de Burgos, Av. Cantabria s/n, 09006 Burgos, Spain.

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|November 27, 2025
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Summary
This summary is machine-generated.

This study introduces an IoT-enabled smart irrigation system using edge computing and machine learning to optimize water use for almond crops. The system enables sustainable agriculture by predicting soil moisture and managing deficit irrigation, even without internet access.

Keywords:
Internet of Things (IoT)almonds smart farmingedge computing in sustainable deficit irrigationprecision agriculturesmart irrigation controllerswireless sensor networks (WSNs)

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Area of Science:

  • Agricultural Engineering
  • Environmental Science
  • Computer Science

Background:

  • Climate change is limiting irrigation water availability, especially in Mediterranean regions.
  • Sustainable agriculture requires efficient water management techniques.
  • Precision agriculture offers solutions for optimizing resource use in farming.

Purpose of the Study:

  • To develop an IoT-enabled edge computing model for smart irrigation systems.
  • To enhance precision agriculture for almond cultivation.
  • To implement Controlled Deficit Irrigation (CDI) strategies efficiently.

Main Methods:

  • Utilized IoT sensors to gather meteorological, soil humidity, and crop data.
  • Developed a hybrid machine learning (ML) model for real-time soil moisture prediction.
  • Implemented an edge computing approach, avoiding cloud dependency for data processing.

Main Results:

  • The ML model accurately predicts soil moisture for smart irrigation.
  • The system enables the application of Controlled Deficit Irrigation (CDI) with 35% reduction in crop evapotranspiration (ETc).
  • Real-time crop anomaly detection was achieved without cloud computing.

Conclusions:

  • The proposed IoT-enabled edge computing model enhances irrigation efficiency and sustainability in almond farming.
  • This methodology facilitates precise water management, even in remote areas lacking internet connectivity.
  • The study is a foundational step towards integrating ML algorithms into agricultural irrigation strategies.