IoT-driven smart irrigation system to improve water use efficiency.

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.

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.

Developing a centralized automatic control system to increase flexibility of water delivery within predictable and unpredictable irrigation water demands

Food and water security: Analysis of integrated modeling platforms

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.

Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review

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.

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.

Food and water security are critical challenges in Pakistan, exacerbated by rapid population growth, climate variability, and limited resources. This study explores the application of machine learning techniques to address these issues. We specifically examine the dimensions of food and water security in Pakistan, employing data-driven methods to enhance crop yield predictions, food production forecasting, and water resource management. Using secondary data, we refine machine learning models, such as random forest and linear regression, to analyze water availability, crop yield, and crop production. These models aim to optimize resource distribution, improve irrigation efficiency, and minimize water waste. We propose developing AI-based predictions to address food and water crises proactively. Our findings indicate that food insecurity persists in Pakistan, worsened by uneven distribution. Given the country’s high dependence on irrigation for crop production, we analyze the impact of population growth on food production and water demand. We recommend a comprehensive strategy that includes infrastructure development, improved water use efficiency in agriculture, and policy adjustments to balance food imports and exports.

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.

Urban areas face significant challenges, including a lack of green spaces, scarce water resources, environmental pollution, and elevated heat emissions, particularly in developing countries experiencing rapid population growth. Therefore, the study aims to advance sustainable urban agriculture by designing and evaluating a solar-powered smart rooftop irrigation system for peppermint cultivation. The system incorporates two drip irrigation setups—conventional and smart irrigation—powered by photovoltaic (PV) panels. The smart system integrates real-time monitoring of critical variables, including (1) soil moisture, (2) relative humidity, (3) PV panel temperature, and (4) PV panel current and voltage. Key performance metrics such as water and energy consumption, water use efficiency, energy productivity, and carbon dioxide emissions were evaluated for both systems. In addition, the economic analysis of the smart system was determined. Results revealed that the smart system reduced water and energy consumption by 28.1% compared to conventional irrigation. Additionally, the smart system achieved a notable reduction in carbon footprint, with CO2 emissions of 0.181 kg CO₂/m2/year compared to 0.252 kg CO₂/m2/year for the conventional system. The system’s economic analysis demonstrated a payback period of 5.6 years, highlighting its financial viability. This study underscores the transformative potential of solar-powered smart irrigation systems in enhancing food security, conserving water, reducing energy consumption, and mitigating carbon emissions in urban agriculture.

A review of food and water security in the context of sustainable development is the purpose of this study. Food and water security are complicated sustainable development challenges that are linked to both health and sustainable economic development through malnutrition. These are contained in the sustainable development SDGs such as 2 and 6 (Zero Hunger) (Sanitation and clean water). This paper is a review of food and water security that has to do with the conceptual issues, stylized facts on food and water security, food and water security nexus, factors militating against food security around the world, related empirical studies and way forward, Having pointed out some of the factors militating against food and water security such global warming/ climate change, disease outbreak and insecurity etc. strong conclusion and recommendation were made such as fight against insecurity and diseases outbreak, good sanitation and hygiene should also be promoted and sustained, good agricultural policy formation and implementation amongst other things will play out to promote food and water security, hence, to achieve sustainable economic development.

Agriculture is transitioning from traditional methods to precision-based approaches supported by digital technologies and smart systems. A key innovation in this transformation is precision agriculture where fertigation plays a crucial role by integrating water and nutrient management into a real-time and site-specific approach. Recent advances in precision fertigation such as IoT (Internet of things)-based sensors could improve water use efficiency (WUE) by 61–64.1% and increase crop yield by 12–35%. Irrigation based on time-domain reflectometery (TDR) approach could increase WUE by 40–56%, while GreenSeeker technology may enhance nutrient use efficiency (NUE) by 20–45%. Drip fertigation improved WUE by 9–70% and NUE by 16.5–29% and improvised soil enzyme activity such as catalase (2.81–93%), urease (1.84–31%) and phosphatase (5.34–61%). Despite these benefits, challenges such as high initial investment, environmental variability data management issues, cybersecurity concerns, limited technical knowledge, infrastructure gaps, interoperability problems and the lack of field-specific calibration issues persist. This review examines technological advancements, agronomic principles and field-level applications of precision fertigation, highlighting its contributions to enhance crop productivity and maintain long-term soil health. Drawing upon 266 relevant studies and innovations over last 2 decades, this review elaborates the implementation challenges, research gaps and future directions in scaling precision fertigation within diverse agro-ecological settings. Additionally, it examines the economic implications and policy frameworks necessary to facilitate widespread adoption, particularly in smallholder farming systems. Emphasis has been placed on the role of components and their integration with advance technology in optimizing fertigation scheduling and minimizing environmental footprints. Ultimately, this study underscores precision fertigation as a promising approach for resilient, sustainable and climate-smart agriculture.

Agriculture is a vital sector in the global economy but also a major contributor to water consumption and wastage due to inefficient irrigation techniques. To address this issue, smart irrigation systems using the Internet of Things (IoT) have emerged as a solution for optimizing water use. These systems utilize real-time sensor data to improve irrigation efficiency and agricultural productivity. This paper presents an automatic, low-cost intelligent irrigation system based on a fuzzy rule-based inference approach and an energy-aware routing algorithm. The proposed system determines the optimal irrigation method using sensor data and ensures efficient information transmission through a fast fuzzy-based routing mechanism. Additionally, it enables remote monitoring and control via mobile devices, enhancing user convenience. The system is designed to be intelligent, cost-effective, and portable, making it suitable for various agricultural applications such as greenhouses and farms. Simulation results demonstrate that the proposed method outperforms existing algorithms, including DLQR, SPIS, and FWIS, in terms of network lifetime and power consumption. By improving water efficiency and reducing resource wastage, this research contributes to sustainable agriculture. The proposed system provides a scalable and adaptable solution for modern farming, ensuring better irrigation management while conserving essential resources.

Facing Global Environmental Change