Intelligent and automatic irrigation system based on internet of things using fuzzy control technology

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. 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. 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. 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. 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.

Agriculture accounts for approximately 24.23% of total GDP and 22% of total exports in Nigeria. It is the most important occupation, providing a source of income for the majority of rural dwellers in Nigeria. Water is the most important resource for agriculture, and irrigation is still one of the most basic wateracquisition processes. Previously, irrigation procedures were carried out manually, resulting in a significant waste of time and an inaccurate volume of water deployed at any given time. In recent times, an artificial intelligence (AI)-based irrigation management method using Internet of Things (IoT) has gained prominence. The irrigation industry has taken advantage of this new technology called Internet of Things to improves irrigation management and drastically reduces operating expenses related to infrastructure maintenance. One of the most serious issues confronting smart irrigation systems is stakeholders' inability to convert available data into detailed and accurate information that can be used in decision making, particularly when it comes to water waste due to improper timing and the proportion.With water scarcity and inefficient traditional irrigation methods posing significant challenges to agricultural productivity,IoT-based technology offers a sustainable solution to manually operated irrigation systems. IoT-based smart irrigation system is an efficient farmland preparationtool and to managing scarce resources such as water and time.Based on the Internet of Things technology, the study analysed key parameterssuch as soil moisture, temperature, and water management using IoT-based technique that work with various sensors. The temperature, humidity, plant and soil moisture sensors are used in the design to detect different soil conditions and automatically irrigate the farmland based on the soil moisture contentand the plant requirements. The results demonstrated the effectiveness of the IoT-based smart irrigation system in optimizing water use in scarcity and enhancing crop yields.

Water management in agriculture has been transformed by smart irrigation systems that use the Internet of Things (IoT) to maximize resource use and boost crop yields. IoT-based irrigation, which reduces waste and improves sustainability in the face of growing water scarcity, combines sensors, actuators and real-time data analytics to deliver accurate water flow. The use of IoT in agriculture is reviewed in this paper, which also covers AI-driven decision-making algorithms and communication technologies like LoRa, Zigbee and Wi-Fi. In agriculture, IoT has been widely employed in agriculture to enable better farming and redefine conventional practices. Some of the necessary applications include monitoring crops, monitoring livestock, automation of the supply of water through real-time data, promotion of optimal water consumption and wastage minimization. Furthermore, increased agricultural yields, cost savings and water conservation are just a few benefits of using IoT in irrigation systems. Research also claimed that when compared to traditional methods, IoT-based irrigation systems can save up to 30% on water usage. IoT-based irrigation has drawbacks despite its benefits, including costly upfront costs, complicated technology and cyber security threats. The use of self-powered sensors, AI-powered predictive irrigation and blockchain-enhanced data security are some of the upcoming trends. Smart irrigation systems have the ability to transform precision agriculture and guarantee both environmental preservation and food security by removing implementation obstacles. Future research should focus on enhancing interoperability among IoT devices, improving decision-making algorithms and developing cost-effective solutions for small-scale farmers. With continuous innovation and widespread adoption, IoT-driven smart irrigation has the potential to address global food security concerns while preserving water resources, creating a more sustainable and technologically advanced agriculture industry.

Irrigation management in several developed countries now uses modern technology by utilizing the capacity of the Internet of Things and Big Data for leak detection, water measurement, planning, monitoring and distribution. The Internet of Things provides new solutions for the irrigation sector and helps improve irrigation management and reduce operational costs associated with maintaining infrastructure. One of the biggest problems facing smart irrigation systems in Indonesia is the inability of stakeholders to convert available data into in-depth and accurate information that can be used in decision making. The purpose of writing this article is to prepare the concept of building a smart irrigation system for the sustainable use of water for stakeholders. Analysis and approaches are carried out by reviewing the development of smart irrigation systems from the perspective of Industry 4.0 (big data and internet of things), identifying the use of IoT-based technology, innovation and data-science best practices that can transform organizations and institutions, irrigation users become more data-centered centric artificial intelligence. The results of this study propose innovative simple semantic solutions to help irrigation users or farmers to measure humidity, rainfall, wind speed, soil temperature and solar radiation in real-time through mobile application information to the water user community.

Objective of the study to find out irrigation management in conserving the water resources with irrigation system to increase crop productivity. In this paper, this has designed and implemented an IoT-based smart irrigation system using soil moisture, pH, and NPK sensors for remote monitoring and control of soil parameters, by interfacing them with the NodeMCU ESP8266 microcontroller. The output values obtained from the sensors were displayed using an LCD and values were then sent to a cloud server for remote access. Research also interfaced a relay module with a water pump to water the plants automatically when moisture content is lower than a set threshold. The results indicate that the soil moisture sensor's values, NPK sensors and pH sensor are well correlated with the lab values with an error of less than 3%, 5% and 2% respectively. The comparison of the results with the manual practice of irrigation demonstrated a considerable difference in the water and fertilizer consumption with the implementation of IoT assistance in the irrigation system. Therefore, this study confirms that the proposed model is precise, accurate, cost-efficient, and easily scalable for practical applications in smart agriculture by eliminating wastage and real-time monitoring of required inputs.

Climate change is driving new solutions to manage water more efficiently. Such solutions involve the development of smart irrigation systems where Internet of Things (IoT) nodes are deployed throughout large areas. In addition, in the mentioned areas, wireless communications can be difficult due to the presence of obstacles and metallic objects that block electromagnetic wave propagation totally or partially. This article details the development of a smart irrigation system able to cover large urban areas thanks to the use of Low-Power Wide-Area Network (LPWAN) sensor nodes based on LoRa and LoRaWAN. IoT nodes collect soil temperature/moisture and air temperature data, and control water supply autonomously, either by making use of fog computing gateways or by relying on remote commands sent from a cloud. Since the selection of IoT node and gateway locations is essential to have good connectivity and to reduce energy consumption, this article uses an in-house 3D-ray launching radio-planning tool to determine the best locations in real scenarios. Specifically, this paper provides details on the modeling of a university campus, which includes elements like buildings, roads, green areas, or vehicles. In such a scenario, simulations and empirical measurements were performed for two different testbeds: a LoRaWAN testbed that operates at 868 MHz and a testbed based on LoRa with 433 MHz transceivers. All the measurements agree with the simulation results, showing the impact of shadowing effects and material features (e.g., permittivity, conductivity) in the electromagnetic propagation of near-ground and underground LoRaWAN communications. Higher RF power levels are observed for 433 MHz due to the higher transmitted power level and the lower radio propagation losses, and even in the worst gateway location, the received power level is higher than the sensitivity threshold (−148 dBm). Regarding water consumption, the provided estimations indicate that the proposed smart irrigation system is able to reduce roughly 23% of the amount of used water just by considering weather forecasts. The obtained results provide useful guidelines for future smart irrigation developers and show the radio planning tool accuracy, which allows for optimizing the sensor network topology and the overall performance of the network in terms of coverage, cost, and energy consumption.

ABSTRACT: This study explores how smart irrigation systems can be improved by introducing advanced technologies and reducing water consumption to fight climate change. This study aims to identify the factors affecting the success of smart irrigation systems based on the Internet of Things with the mediation of optimal consumption management. This is an applied research employing mixed methodologies (qualitative-quantitative). Initially, the semi-structured interviews were carried out to obtain the effective success factors of the smart irrigation system. Analysis in the qualitative section has been conducted using the Maxqda software. For the quantitative study, a 25-statement questionnaire was applied according to the selected codes obtained with a five-point Likert scale to validate the obtained model. The questionnaire was distributed online in January 2023, and analysis was conducted using SmartPLS3 software. The technical aspects of the questionnaire were assessed using validity and reliability criteria, which can guarantee the precision of the research findings. Construct and content validity were employed in this study to examine the questionnaire’s validity. The researchers employed Cronbach’s alpha coefficient to evaluate the reliability of the measurement instrument. Besides, it can be said that the research instrument has acceptable reliability because obtained Cronbach’s alpha for all variables was greater than 0.70 and the questionnaire’s overall alpha was determined to be 0.810. Furthermore, the t-statistics for all research hypotheses is higher than 1.96 at the 95% confidence level. In this sense, the hypotheses of the research were confirmed. The Internet of Things and will change the nature of activities and services in the market. In fact, for emerging markets, the untapped and growing investment opportunities and the economic leap against the Internet of Things are so enticing and facilitating that it is impossible to resist. and neglecting it will cause irreparable damage to agility. Therefore, the success of the Internet of Things for emerging markets depends on the preconditions of integration of activities carried out by decision-making organizations, facilitation of regulations, and communication and interaction between relevant sectors, which should be considered a priority through cross-sectoral research.

The current global water crisis, caused by factors such as population growth, urbanization, and climate change, has a significant impact on agriculture, which consumes 70% of the world's freshwater. One potential solution to this problem is the use of intelligent irrigation systems. Cloud-based smart irrigation systems offer a more efficient and cost-effective approach to water consumption management. This study examines the concept of cloud-based smart irrigation systems, their advantages, and their potential application in agriculture. To begin, the authors detail the various components of a cloud-based smart irrigation system, including sensors, controllers, and cloud computing. They then explore the benefits of cloud-based systems, which include scalability, cost-effectiveness, and real-time data processing capabilities. They also delve into the different types of sensors used in smart irrigation systems, such as soil moisture, weather, and crop sensors, as well as their respective advantages and limitations. Furthermore, they discuss the various controllers utilized in smart irrigation systems, such as scheduling, sensor-based, and weather-based controllers. They elaborate on how these controllers function and the advantages they offer in terms of water conservation and crop yield optimization. Lastly, they examine the practical application of cloud-based smart irrigation systems in agriculture, including how to create, implement, and tailor the system to suit the specific requirements of a particular farm. They also consider potential barriers to adoption, such as cost and technological complexity, and how to overcome them. In short, cloud-based smart irrigation systems present a promising solution to the water crisis in agriculture. These systems can significantly reduce water waste, increase crop yield, and save costs by utilizing cloud computing technology to manage irrigation. With careful planning, installation, and configuration, cloud-based smart irrigation systems have the potential to be an effective tool for farmers in improving their productivity and sustainability.

The design and evaluation of a smart irrigation system leveraging Internet of Things (IoT) technology is presented to address Jordan’s severe water scarcity challenges. The system integrates soil moisture and temperature sensors, the Arduino MKR WiFi 1010 microcontroller for real-time data processing, and a cloud platform for data management and remote control. Optimizing water delivery to crops based on real-time environmental data, the system reduces water waste and enhances agricultural productivity. Field tests in controlled and real-world settings confirmed its efficacy, highlighting IoT’s transformative role in achieving sustainable irrigation practices and addressing global water challenges.

Today the use of Internet of Things (IoT) applications increasing rapidly to use automation in the areas including home, hospital, office, and others. In the future, the people expected to use IoT applications in the year 2025 by 11 trillion dollars business worth with use. The problem is to develop an Intelligent IoT system application based on user specifications, and the demand for application with the use of elements, models, and providing services. The objective of the paper is to explore IoT elements, framework-architecture, analysis, and monitoring, and case study applications, such as, Heath care System, Pilotless plane, Smart lighting, Home IDS, Smart Parking, Smart Irrigation, and Intelligent Transport System applications. Finally, effective utilization of elements, protocols, components, and sensors networks, AI applications, and Machine learning applications predict the future patterns based on present and past data of applications. The conclusion of the proposed model improves the quality of the IoT system.

The necessity for effective water management systems has increased recently due to the rising demand for water resources and the negative effects of climate change. This chapter gives a thorough investigation into the installation of a water management system (WMS) using machine learning (ML) and the internet of things (IoT) technologies to address these issues. The proposed WMS makes use of internet of things (IoT)-enabled sensors placed throughout various water infrastructure sites, including reservoirs, water supply networks, and pipelines to gather real-time information on critical variables like weather conditions, water quality, etc. The acquired data is then subjected to sophisticated ML algorithms to optimize water use and distribution. The WMS described in this chapter serves as an example of how ML and IoT have the potential to fundamentally alter current approaches to water management.

Irrigation systems are becoming increasingly important, owing to the increase in human population, global warming, and food demand. This study aims to design a low-cost autonomous sensor interface to automate the monitoring and control of irrigation systems in remote locations, and to optimize water use for irrigation farming. An internet of things-based irrigation monitoring and control system, employing sensors and actuators, is designed to facilitate the autonomous supply of adequate water from a reservoir to domestic crops in a smart irrigation systems. System development lifecycle and waterfall model design methodologies have been employed in the development paradigm. The Proteus 8.5 design suite, Arduino integrated design environment, and embedded C programming language are commonly used to develop and implement a real working prototype. A pumping mechanism has been used to supply the water required by the soil. The prototype provides power supply, sensing, monitoring and control, and internet connectivity capabilities. Experimental and simulation results demonstrate the flexibility and practical applicability of the proposed system, and are of paramount importance, not only to farmers, but also for the expansion of economic activity. Furthermore, this system reduces the high level of supervision required to supply irrigation water, enabling remote monitoring and control.

Proper monitoring and control of irrigation and fertilization system is crucial in agriculture field to ensure sufficient nutrients and moisture supplied to the plant is maintained all the time. There are two type of parameters being monitored which are soil moisture and its pH level. A systematic approach in monitoring and control of these parameters is thus necessary to uphold sustain smart farming solutions. Main objective of this project is to design smart irrigation and fertilization system for chili plant using Fuzzy Logic. In this project, the implementation of Internet of Things (IoT) also included where Wi-Fi node is used for the means of connection medium. Fuzzy Logic was implemented as a controller in this system to administer the flowrate of water, alkali and acid solutions into the soil in order to maintain its moisture and pH level. There are 2 memberships assigned as input fuzzy which are moisture and pH value while output have 3 memberships which are alkali, neutral and acid solution flowrate. The fuzzy rules were programmed into Arduino to control the water pump and valve opening. The system was able to store the data and display on mobile phone through Blynk mobile application. This system was tested on a chili plant where the growth of a plant under controlled environment have better performance compared to the traditional method.

The Internet of Things (IoT) has ushered in a new era of innovative agriculture research. Because IoT is still in its early stages, it must be widely tested before it can be widely deployed in many agricultural applications. In this paper, I look at different prospective IoT applications, as well as the unique concerns and constraints connected with IoT deployment for better farming. The gadgets and wireless communication technologies linked with IoT in agricultural and farming applications are thoroughly researched to focus on the unique requirements. Sensor-enabled IoT systems that deliver intelligent and smart services for smart agriculture are being investigated.
 Several case studies are offered to investigate the existing IoT-based solutions implemented by various organizations, individuals, and groups depending on their deployment criteria. The difficulties in these solutions are addressed, as are the factors for improvement and the future roadmap of work with IoT. Smart farming is a trend that emphasizes the use of information and communications technology (ICT) in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies such as the Internet of Things (IoT) and cloud computing are expected to spur growth and kickstart the usage of robotics and artificial intelligence in agriculture. Such radical departures are upsetting established agricultural practices while also posing several obstacles. This study explores the techniques and equipment utilized in wireless sensor applications in IoT agriculture, as well as the predicted problems encountered when integrating technology with traditional farming practices. Furthermore, this technical knowledge is useful to growers during crop times ranging from planting to harvest, and applications in packing and transportation are being researched.

Smart agriculture is important in achieving the SDGs, especially food and water. The transition to using smart irrigation systems is highly recommended, considering that this transition can optimize agricultural production. A smart irrigation system is a unified irrigation process integrated with automated technology and IoT (Internet of Things) that drives a new direction of smart agricultural technology development. This study highlights the smart irrigation system as the smart agricultural transition concerning SDGs. The main method was a qualitative review based on a literature study with the criteria for exclusion consisting of indexed journals, review papers or research articles, and publications published within the last decade. The review shows the irrigation control and monitoring used in recent years. Other than that, as a brief report on the current status of IoT-related smart irrigation development, several types of effective smart irrigation that have been done before are compared. Discussed the perspective of SDGs, the goal indicators achieved through smart irrigation showed good results; 11 indicators were achieved. Thus, the challenges and prospects of IoT-related development for smart irrigation are discussed. This study will help researchers and farmers understand clever irrigation more effectively and precisely.