Intelligent Irrigation System Research Articles

Smart Irrigation System using IOT

The majority of nations rely heavily on agriculture to power their economies. A nation's growth is mostly dependent on agriculture, notably for people's livelihood and the production of food and other raw resources. The rise of agriculture is the main driver of a nation's economy. One type of irrigation system that is frequently utilized in the agricultural industry is the smart irrigation system. In areas of farming where water is scarce, irrigation is used. This intelligent irrigation system is designed with farmers in mind. In this paper, the proposed smart irrigation system uses NodeMCU ESP8266. This system reads the values using sensors and waters the plants based on those values. Also, the system will send notification as well as email to the owner for a certain interval of time depending on the owner specification. The owner can also remotely monitor values by using the mobile application or web application. It is very easy to implement, and will save manpower, leading to a cost-effective solution for efficient water management in agriculture. This system harnesses the power of a microcontroller to monitor and control irrigation process, ensuring optimal water usage.

Optimizing water use efficiency in greenhouse cucumber cultivation: A comparative study of intelligent irrigation systems.

This study investigated the use of an intelligent irrigation system for greenhouse cucumber cultivation, aiming to manage water consumption efficiently. During the initial phase, irrigation was tested at four levels: 80%, 90%, and 100% of Field Capacity (FC), and Conventional Flood Irrigation (CFI). Data on environmental conditions and water usage were meticulously recorded. Optimal yields and crop quality (measured by size and firmness) were achieved at CFI and 100% FC, with CFI consuming the most water (0.148 m3/m2) Consequently, 100% FC was identified as the best practice, informing the intelligent system's calibration in the subsequent phase. This adjustment resulted in reduced water consumption and a 15.6% improvement in Water Use Efficiency (WUE) over CFI. Additionally, by examining the product performance and the color characteristics, chlorophyll content, and photosynthesis of the leaves, it was observed that the quality and optimal water supply and the product performance were maintained in the smart irrigation system. The study concludes that, considering long-term outcomes, the intelligent irrigation system is preferable to CFI, offering significant water savings and enhanced WUE without compromising crop quality.

A Holistic Irrigation Advisory Policy Scheme by the Hellenic Agricultural Organization: An Example of a Successful Implementation in Crete, Greece

The aim of this communication article is to present a successful irrigation advisory scheme on the island of Crete (Greece) provided by the Hellenic Agricultural Organization (ELGO DIMITRA), which is well adapted to the different needs of farmers and water management agencies. The motivation to create this advisory scheme stems from the need to save water resources while ensuring optimal production in a region like Crete where droughts seem to occur more and more frequently in recent years. This scheme/approach has three different levels of implementation (components) depending on the spatial level and end-users’ needs. The first level concerns the weekly irrigation bulletins in the main agricultural areas of the island with the aim of informing farmers and local water managers about crop irrigation needs. The second level concerns an innovative digital web-based platform for the precise determination of the irrigation needs of Crete’s crops at a parcel level as well as optimal adaptation strategies in the context of climate change. In this platform, important features such as real-time meteorological information, spatial data on the cultivation type of parcels, validated algorithms for calculating crop irrigation needs, an accurate soil texture map derived from satellite images, and appropriate agronomic practices to conserve water based on cultivation and the geomorphology of a farm are considered. The third level of the proposed management approach includes an open-source Internet of Things (IoT) intelligent irrigation system for optimal individual parcel irrigation scheduling. This IoT system includes soil moisture and atmospheric sensors installed on the field, as well as the corresponding laboratory soil hydraulic characterization service. This third-level advisory approach provides farmers with specialized information on the automated irrigation system and optimization of irrigation water use. All the above irrigation advisory approaches have been implemented and evaluated by end-users with a very high degree of satisfaction in terms of effectiveness and usability.

Experimental performance of smart irrigation systems using IoT

In agriculture field soil is a crucial determinant of plant development, primarily in irrigated environments. Nowadays there are several ways for assessing soil quality on a density or suspense basis. To develop, all plants need a specific amount of moisture level. PI involves cutting-edge technologies such as the Internet of Things (IoT), Wireless Sensor Networks (WSN), and cloud computing. In this method presents an overview of the soft computing methods based on the PI concept and architecture, including the most common wireless technologies. Then, a real-time IoT-based intelligent irrigation system is designed as a proof of concept. Several wireless sensor nodes are deployed to monitor both soil moisture and temperature. Sensed data are transmitted to the gateway through the Messaging Queuing Telemetry Transport (MQTT) communication protocol. Root based findings depict that the proposed work increases crop growth and productivity and decreases water wastage more than other state-of-the-art strategies. ANFIS method to predict the plant growth level based on the fuzzy rule. Wireless communication technology allows for the automation of different devices and real-time analysis of data collected by these sensors. The IoT (Internet of Things) system demonstrates improved plant growth. Furthermore, the application used in the plant's worst conditions and situations has provided the best sources for appropriate plant growth..

Proposed Intelligent Irrigation System for Riyadh City Using Fuzzy Logic

Considering the insufficient rainfall and rapid evaporation of soil moisture in desert regions, irrigation becomes very challenging in Riyadh. Automation is therefore required for optimum productivity and water conservation. According to the vision of the Green Riyadh project, recycled water will be used in the irrigation system to irrigate all green lands. The method of irrigation and the quantity of water being used must both be considered. Since drought inhibits plant growth and excessive moisture limits plants' ability to absorb nutrients and raises the possibility of disease development, only the amount of water needed by plants should be used. Artificial intelligence and fuzzy logic are increasingly seen as solutions to be implemented in smart drip irrigation systems. The fuzzy logic control system will aid in water conservation given its shortage, which has become a major worldwide concern. The system also has the advantage of conserving moisture to counteract inadequate rainfall, saving electricity and reducing labor costs. For such advantages, an intelligent irrigation control system based on fuzzy logic adapted to the climate of Riyadh will be proposed. Based on the measured soil moisture, ambient temperature, air humidity and solar irradiance, the fuzzy controller calculates the necessary irrigation duration. The features of the fuzzy logic toolbox in MATLAB are used to create the proposed system.

Fuzzy Logic Controller-based Intelligent Irrigation System Using Solar Radiation Data

Solar radiation is a critical factor influencing agricultural productivity and water resource management. Irrigation systems play a pivotal role in maintaining crop health and yield, and optimizing their operation requires accurate solar radiation data. This abstract explores the significance of solar radiation data in enhancing the efficiency of irrigation systems. Irrigating agricultural fields using an intelligent information system plays a crucial role. This study introduces an irrigation control system employing closed-loop control to use the available water resources efficiently. Continuous data collection from field sensors was done and transmitted to a central station in wireless mode. The data was then retrieved and processed in a computer-based or microcontroller-based solution model, enhancing system autonomy, reliability, and cost-effectiveness. Weather conditions are translated into fuzzy set values. The pump, water outlet valves, and sprinklers are set into motion according to control commands. This research simplifies the need for manual labor and reduces water wastage.

Artificial intelligence: prototype of an automated irrigation system for the cultivation of roses in Cotopaxi

Implementing artificial intelligence in agriculture can improve efficiency, reduce pollution, and promote more effective agricultural production. Efficient irrigation management avoids wasting water and ensures that plants receive the right amount of water at the right time. The purpose of this research is to present an intelligent irrigation system based on neural networks and fuzzy logic, to avoid the presence of pests due to excess relative humidity in rose crops in Cotopaxi. A mixed methodology was used. The SCRUM methodology, Android Studio as an integrated development environment, a relational database management system and the Mobile-D method were used as software elements. For the prototype construction, the main hardware element that was used was the Arduino Board. The system for irrigating automated water using fuzzy logic took less time than manual irrigation. Training actions were proposed for employers and employees in the use and maintenance of the automated irrigation system, to maintain continuous improvement in the process

AgroSense: An IoT-Based Manual Crops Selection Farming

This capstone project introduces an Intelligent Irri-gation System leveraging IoT technology to enhance agriculture. Using the ESP32 microcontroller and various sensors for soil moisture, water levels, and environmental conditions, the system automates irrigation based on real-time data. It communicates through the Blynk platform, allowing remote monitoring via a mobile app. The project includes a smart algorithm for crop selection and irrigation control, displayed on an LCD and acces- sible through the Blynk app. By considering soil moisture and water availability, the system adapts to different crops like rice, wheat, potato, and corn. The project promotes sustainability by optimizing water usage and encourages efficient crop growth. The integration of a manual crop count for field feedback enhances decision-making. Overall, this system presents a user-friendly and innovative solution for precision agriculture, showcasing the transformative potential of IoT, data analytics, and machine learning in modernizing farming practices.

Development of IoT based intelligent irrigation system using particle swarm optimization and XGBoost techniques

A crop needs regular watering throughout its life to grow well. Irrigation improves food growth. Machines irrigate plants. The dry Sahel, which gets a lot of rain during the summer season but is dry in winter, needs irrigation. When it doesn't rain enough, crops need watering. By constantly monitoring soil moisture, humidity, temperature, and pH, precision agriculture reduces water use and increases crop output. Precision gardening uses less water. In many wealthy nations, efficient farming requires the internet of things (IoT). Particle swarm optimization (PSO) and XGBoost are used in this IoT-based intelligent watering system. Humidity and moisture sensors gather soil data at grass roots. Sensors constantly gather this data. These data are useless for smart watering. PSOselects smart watering data. This reduces central cloud info storage. Then, machine learning methods are trained using soil humidity, moisture, crop, and weather data. These programs can calculate a crop's water requirements. IoT devices control irrigation system water flow and results in saving fresh water. XGBoost algorithm is saving water from 23% to 27% for different crops.

Solar-Powered GSM Irrigation for Intelligent Water Management

Efficient water management is crucial for sustainable agriculture and landscaping. This project introduces a novel solution, combining solar power and GSM technology to create an intelligent irrigation system. Integrated GSM connectivity enables remote monitoring and control, allowing users to adjust irrigation schedules and settings from anywhere, enhancing convenience and flexibility. By leveraging data analytics and sensor feedback, the system optimizes water usage, ensuring precise delivery based on plant needs and environmental conditions. This approach not only conserves water but also promotes healthier plant growth and higher yields. The integration of GSM technology ensures real-time communication and alerts, allowing users to respond promptly to changing conditions and unforeseen events. Through case studies and performance evaluations, the presentation will demonstrate the system's reliability, durability, and cost- effectiveness, underscoring its viability for widespread adoption. Attendees will gain insights into how solar- powered GSM irrigation can revolutionize water management practices, empower farmers and gardeners, and contribute to building resilient, sustainable ecosystems in a rapidly changing world.

Smart Automated Irrigation System using Wireless Technology

Abstract: The need for agricultural output has surged due to the exponential rise of the world population, resulting in a strain on water supplies and a need for more effective irrigation systems. The goal of this project is to optimize water utilization in agricultural settings by presenting an automated and intelligent irrigation system. Based on current soil moisture levels, the system monitors and regulates irrigation using soil moisture sensors, an Arduino Nano, and a Raspberry Pi 3B+. By converting analog signals from the soil moisture sensor into digital data, the Arduino Nano serves as an analog-to-digital converter. This digital data is sent to the Raspberry Pi 3B+, which acts as the central control unit. A MOSFET is then triggered to activate a relay that is coupled to a 5V DC water pump when the moisture levels drop below a certain threshold. The system also has wireless connection, which enables remote control and monitoring via an Android application. Users have the ability to manually override the automatic system if needed, monitor the moisture content of the soil, and turn on or off the water pump. This feature improves the usability and flexibility of the system.

Application of Internet-of-Things Wireless Communication Technology in Agricultural Irrigation Management: A Review

The integration of Internet-of-Things technology with traditional agricultural irrigation is a crucial factor in the advancement of traditional agricultural irrigation towards smart irrigation. Despite the widespread use of conventional irrigation methods in many areas, they lead to the significant wastage of both human and water resources. Therefore, the development of energy-saving and efficient intelligent irrigation systems through the application of Internet-of-Things technology and wireless communication technology is the way forward. This paper summarizes the common wireless communication technologies in the agricultural Internet of Things: Fifth-generation, WiFi, ZigBee, LoRa, and NB-IoT. The research status of the above wireless communication technology in agricultural irrigation management is discussed, and the agricultural irrigation management example using the above wireless communication technology is also presented. The advantages and limitations of the application of the above wireless communication technology in agricultural irrigation management are sorted out. Finally, this paper analyzes the challenges of data security issues, data fusion problems, intelligent irrigation system costs, power and energy problems, and system equipment failures faced by the use of IoT wireless communication technology in agricultural irrigation management. This review aims to assist researchers and users in choosing the most suitable wireless communication technology for diverse applications.

Variation of leaf turgor and pressure parameters evaluation in drip-irrigated apple canopy

Leaf turgor pressure is a relevant metric for determining plant water content. To diagnose an apple tree water shortage, it is critical to precisely establish the features of leaf turgor pressure change in the canopy. In the current study, we continually monitored the leaf turgor pressure parameter (Pp) at different azimuthal, vertical, and radial locations of the apple canopy based on leaf patch clamp pressure (LPCP) probes. The results demonstrated that the Pp curves on sunny and rainy days were significantly different. A peak occurred on sunny days, during which the turgor pressure remained constant around midday. Under full irrigation, there was a greater change rate and daily maximum of Pp (maxPp) at the east (azimuthal), upper layer (vertical), and distal (radial) positions. While leaf turgor pressure dramatically decreased with incomplete watering, maxPp significantly increased at the central and lower layers of the east canopy, as well as on the proximal and middle of the radial parts. This spatial heterogeneity in canopy leaf turgor pressure was related to the soil water potential, midday leaf water potential, sponge tissue thickness, and canopy solar radiation. Then, the ideal drought stress indicator parameter (maxPp) and canopy turgor monitoring leaf location (the middle position of the eastern canopy central layer's radial branch) were determined by multiparameter assessment. The findings presented above serve as a theoretical foundation for the construction of an intelligent irrigation system based on apple tree water status monitoring.

Creation of an intelligent irrigation system based on the fuzzy Sugeno model

This paper discusses the creation of an intelligent irrigation system based on the fuzzy Sugeno model. The goal of the work is to develop an effective system capable of automatically managing irrigation in agriculture, horticulture and other areas where optimal use of water resources is required. To achieve this goal, an analysis and selection of data processing methods was carried out, and the key parameters necessary for the implementation of an intelligent irrigation system were identified. The fuzzy Sugeno model was chosen as the base model, which allows taking into account the uncertainty and fuzziness of data when making decisions. The main objective of the work was to create software capable of making a decision on the need for irrigation and the optimal volume of water supply based on the collected data on soil moisture. Research has shown that the developed system is capable of effectively managing irrigation, optimizing the consumption of water resources and increasing crop yields. The results of the work can be applied in agriculture, horticulture and other areas where automated irrigation control based on soil moisture data is required.

High-Technology Agriculture System to Enhance Food Security: A Concept of Smart Irrigation System Using Internet of Things and Cloud Computing

CONTEXT: Food security is highly reliant on agricultural activity to drive the world economy. However, this activity is in great danger due to climatic changes and improper use of irrigation techniques. Consequently, the lives of numerous individuals worldwide are in jeopardy. In light, this paper investigates the promise of smart irrigation systems based on new technology. OBJECTIVE: To meet the growing demand for water in agriculture, this study presents an intelligent irrigation system that uses cutting-edge technologies of 1) cloud computing, 2) embedded systems, and 3) Internet-of-Things (IoT). The main objective is to demonstrate how this innovative strategy can effectively manage water resources, supporting food security through cutting-edge agricultural technology. METHODS: This paper proposes a smart irrigation system based on cutting-edge technologies like the embedded system, Internet of Things (IoT), and cloud computing as a groundbreaking strategy to improve food security through the implementation of advanced agricultural technology. This system supervises real-time monitoring of crucial environmental factors such as 1) moisture, 2) humidity, 3) temperature, and 4) water levels, in smart agriculture practices. In addition, this system employs the latest sensors, including the module (DHT22), water level sensor, and moisture sensors, which are connected to the widely used embedded system (ESP32). The system uses the ThingSpeak cloud and ThingView app to enable wireless communication between the device and the farm owner, enhancing their interaction. The automated control of the two water pumps is based on the readings of various environmental factors. Moreover, this will also present a mathematical-driven function known as linear interpolation to calibrate the water level sensor in percentage. This system was created using the V-model software development approach. RESULTS AND CONCLUSION: Farmers can access comprehensive farm data from anywhere in the world as the sensor data is transmitted in real-time to both the ThingSpeak cloud and the ThingView. This capability allows for more precise crop irrigation and increased production. The study's findings demonstrate a striking 70% reduction in water consumption for soil irrigation when utilizing the proposed smart irrigation system. This paper underscores the significant promise of smart irrigation systems, driven by IoT, embedded systems, and cloud computing, to conserve water resources and advance food security. SIGNIFICANCE: This article proposes an innovative solution that reduces soil irrigation water consumption by 70% compared to traditional methods. It explores how smart irrigation can improve the sustainability of agriculture and positively influence food security.

Internet of things sensors and support vector machine integrated intelligent irrigation system for agriculture industry

Because there is more demand for freshwater around the world and the world’s population is growing at the same time, there is a severe lack of freshwater resources in the central part of the planet. The world’s current population of 7.2 billion people is expected to grow to over 9 billion by the year 2050. The vast majority of freshwater is used for things like cooking, cleaning, and farming. Most industrialised countries are in desperate need of smart irrigation systems, which are now a must-have because of how quickly technology is improving. In article presents IoT based Sensor integrated intelligent irrigation system for agriculture industry. IoT based humidity and soil sensors are used to collect soil related data. This data is stored in a centralized cloud. Features are selected by CFS algorithm. This will help in discarding irrelevant data. Clustering of data is performed by K means algorithm. This will help in keeping similar data together. Then classification model is build using the SVM, Random Forest and Naïve Bayes algorithm. Model is trained, validated and tested using the acquired data. Historical soil and humidity related data is also used in training the model. K-means SVM hybrid classifier is achieving better results for classification, prediction of water demand and saving fresh water by intelligent irrigation. K-means SVM hybrid classifier has achieved accuracy rate of 98.5 percent. Specificity, recall and precision of K-means SVM hybrid classifier is also higher than random forest and naïve bayes classifier.

Economical Design of Drip Irrigation Control System Management Based on the Chaos Beetle Search Algorithm

In the realm of existing intelligent drip irrigation control systems, traditional PID control encounters challenges in delivering satisfactory control outcomes, primarily owing to issues related to non-linearity, time-varying behavior, and hysteresis. In order to solve the problem of the unstable operation of the drip irrigation system in an intelligent irrigation system, this paper proposes chaotic beetle swarm optimization (CBSO) based on the BAS (beetle antennae search) longicorn search algorithm, with inertial weights, variable learning factors, and logistic chaos initialization improving global search capabilities. This was accomplished by formulating the optimization objective, which involved integrating the control input’s time integral term, the square term, and the absolute value of the error. Subsequently, PID parameter tuning was performed. In order to verify the actual effect of the CBSO algorithm on the PID drip irrigation control system, MATLAB was used to simulate and compare PID control optimized by the GA algorithm, PSO algorithm, and BSO (beetle search optimization) algorithm. The results show that PID control based on CBSO optimization has a short response time, small overshoot, and no oscillation in the steady state process. The performance of the controller is improved, which provides a basis for PID parameter setting for a drip irrigation control system.

A Model of a Smart Garden Using the Integration of a Set of Components

The purpose of this paper is to describe an experiment in the design and construction of an intelligent irrigation system based on the integration of ready-made programmed components and programmable ones, which, if necessary, will provide watering of plantations. This paper presents a model of an integrated multi-component architecture for a smart garden, which is based on the combination of various components and techniques in small-scale urban garden irrigation by using Internet of Things (IoT) technologies. Automation is related to planning based on sensor data processing, determining when to activate water supply. Unlike manufacturers who offer "smart irrigation" solutions with all the automated components needed to build a complete intelligent system, our approach is different. We combine components from various manufacturers to create an independent irrigation system. The challenge lies in ensuring these components can seamlessly work together, processing automation instructions through external software, and storing data on a remote server. The described model represents an innovative solution that enhances the functionality and sustainability of urban gardens by combining an understanding of the gardens' needs and effective resource management, contributing to an improved quality of life for citizens and the sustainable use of natural resources.

Construction of an intelligent agricultural irrigation control platform based on PLC technology

Abstract This paper firstly constructs a PLC-based intelligent irrigation control system, analyzes the requirements of its system functions, and determines three major modules of the system: data acquisition module, intelligent irrigation module, and Web service module. Then the system fuzzy control process is determined. According to the moisture value collected by the soil moisture sensor, the average is taken, and the deviation and deviation change rate is obtained by calculating the difference with the set value, and the control value is obtained by querying the previously deposited fuzzy control table through a series of transformations, and the command is executed according to the program setting. The automatic irrigation requirement is achieved by controlling the solenoid valve on and off. Finally, the analysis of system functions in terms of sensor accuracy, system function testing, and temperature and air humidity prediction accuracy was carried out. Regarding sensor accuracy, the error of relative soil moisture content is within 3%, and the relative error of soil temperature is within 0.5. In the system control function test, the solenoid valve will open for irrigation when the soil relative water content is lower than 40% or higher than 70% of the warning range, and the lighting will be turned on when the light intensity is lower than 200 Lux, and the system control is in line with the expectation. The intelligent irrigation system is of great significance to agricultural development.

IOT-Based Smart Irrigation System using DTMF and 8051 MCU

Abstract: In almost every facet of agriculture and gardening, irrigation is the cornerstone activity, with the regular watering of plants and crops paramount to their growth and well-being. However, this essential task often proves burdensome for individuals preoccupied with daily commitments. For farmers, the significance of water supply is further emphasized, as rainwater assumes a critical role in sustaining their crops. While relying on the unpredictability of monsoon rains, canals, and groundwater resources, farmers face the challenges of ensuring a consistent and appropriate water supply, as each crop type necessitates distinct watering regimens. Any insufficiency in providing water to crops can lead to devastating consequences, resulting in the potential destruction of crops and plants. Addressing these challenges and aiming to revolutionize irrigation practices, this paper proposes an IOT-based Smart Irrigation System using DTMF (Dual Tone Multi-Frequency) and 8051 MCU (Microcontroller Unit) as an innovative and transformative solution. This cutting-edge system combines the power of DTMF technology with the versatility of the 8051 microcontrollers, enabling remote control and monitoring of the irrigation process. By leveraging the interactive capabilities of mobile or landline phones, the system allows users, including farmers and gardeners, to conveniently manage irrigation operations from a distance, reducing the need for constant physical presence. This intelligent irrigation system exhibits applicability in automating the irrigation processes of various settings, including gardens, nurseries, and greenhouses. By carefully regulating the water supply to plants based on specific predefined conditions, the system ensures the provision of an optimal and essential amount of water. As a result, the system achieves energy conservation while effectively mitigating any potential water scarcity issues.