An IoT-based Intelligent Irrigation and Weather Forecasting System

Every region of India has a significant agricultural sector. The scope of agriculture is reduced across all of India due to a rapid shift in climate and lesser rainfall. The most productive farming should be done without wasting any water. In the conventional technique, more water than what is required by the crop is used to irrigate the area. Modern irrigation systems like drip irrigation, sprinkle irrigation, etc. can reduce water waste. A sophisticated irrigation device’s execution and design are widely accepted in a variety of settings, with the electric device offering the most dependable pricing performance. This paper proposes an IOT based smart irrigation tracking and management system using Arduino Uno microcontroller. The low-cost dependable gadget is designed to irrigate areas when there is a need for water and to provide data. This paper uses Node-Microcontroller ESP8266, DHT11 sensor and soil moisture sensor. The DHT11 sensor has a humidity measuring component and a NTC temperature component. The soil moisture sensor used for measuring the volumetric water content in the soil. The proposed smart irrigation system reduces wastage of water than the traditional process. The information is sent to the farmers by using cloud website called Blynk app. All the data is uploaded by Wi-Fi module inbuilt in microcontroller to Blynk app cloud database.

With the gradual maturity of the Internet of Things technology, production intelligence and information has become more common. The level of automation in irrigation systems represents a major factor in the efficiency of agricultural development. This article has studied the intelligent automatic irrigation system of balcony flowers based on Internet of Things. MSP430F5438A single-chip microcomputer is used as the core microcontroller to collect soil moisture information through soil moisture sensors. The humidity information is uploaded to the server by the wireless communication module. The server responds to the client’s instructions and the real-time soil temperature and humidity to water the balcony flowers. The GPRS module sends the control command to the lower position machine, and the microcontroller transfers the instructions through the wireless transmission module. And to control the operation of the switch of solenoid valve. The entire irrigation system is based on the MSP430 single-chip microcomputer and has good features such as low power consumption and high stability.

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.

The expansion of agriculture to provide the necessary food is related to the availability of water, but the limited availability of irrigation requires research on techniques to reduce water losses. This paper presents an application of a prototype design of microcontroller based on an intelligent irrigation system which will allow irrigation to take place in the areas. This method can be applied to the system of drip irrigation and its impact on the quantities of water used in irrigation as its application is part of the solution to the problem of water shortage suffered by Libya in addition to reducing the amount of water wasted while irrigating crops. In this study, a network of smart irrigation system was designed for a 5-hectare farm in AL-Sawawa area, located to the east, at about 20 km from Sirte city. The farm was divided into two parts, a vegetable crops section with an area of 3ha and the other section of 2 ha for olive trees. The intelligent irrigation system senses the moisture content of the soil and the temperature of the air through the sensors and turns on or off the water pumps using the relays to carry out this procedure. The main advantage of using this irrigation system is to minimize human intervention and ensure proper irrigation. The microcontroller serves as the main unit of the entire irrigation system, Photovoltaic cells are used to provide solar energy as an energy supply for the whole system. The system is controlled by the microcontroller; it obtains data from the sensors, it compares the data as pre-programmed, and the output signals activate the relays to operate the pumps to start the irrigation process.

Malaysia, has a very conducive environment for agriculture. Six percent of the population are employed to some of the agriculture activities making agriculture the most curtail industry in Malaysia. Hence, there is a need to develop the agricultural facilities by incorporating latest technological advancements. Conventional seeding process is time consuming and requires additional labor cost. In this paper, an automated system is proposed for seeding as well as irrigation process in agriculture which reduces the labor cost. This system aims to increase the efficiency of the seeding process without affecting the nature of soil. The proposed system is equipped with Arduino MEGA and Arduino UNO which acts as the main control unit while ultrasonic and soil moisture sensors are used to detect the obstacles and soil moisture level, respectively. The robot consists of a funnel like arrangement to perform the seeding procedure. The field is equipped with moisture sensors placed at different areas that monitors the moisture level of the soil on a regular interval for irrigation purposes. The proposed system will be of great benefit to the future endeavor of agricultural business as well as it will be able to optimize the seeding and irrigation.

Lack of water results in a reduction in photosynthesis in plants and crops. Plants are significantly affected when the soil water level is depleted thereby resulting in low production in the agricultural sector which can lead to a reduction in food supply. This problem makes water supply and management highly necessary for plants to grow effectively. Over the past century, the rate at which water usage has increased globally has increased at a rate higher than that of population growth. Particularly in dry regions, an increasing number of regions are now using more water than they can sustainably provide. The traditional watering techniques, such as sprinklers and flood mode, are ineffective and those not supply the ideal needs of plants because some plants do not need excess water to grow. This also results in water wasting. These ineffective irrigation systems often provide habitat for organisms that carry illnesses. Research has established that excessive water spillage and stagnant water can be habitat for mosquitoes which can also be dangerous to human health. Therefore, watering plants must be done intelligently, by developing an intelligent system that can regulate the content of water needed to water a plant in accordance with their needs and the moisture content of the soil. This will also reduce the spillage of water. In this study, an automated plant watering system that monitors the soil's moisture level to determine when watering plants is necessary was developed using hardware components such as Arduino UNO (Microcontroller), soil moisture sensor, pump, relays, wires, sprinkler and software instructions to drive the hardware components. An economical watering system was designed. The system was tested and can be effectively used in small gardens and big crop fields.

The role of technology is very important in an automatic watering monitoring system that works based on the YL69 sensor and DHT11 sensor. This study aims to determine the working principle of sensors in a plant watering monitoring system with mobile applications (Blynk) and thingspeak web. Thingspeak web design aims to process data recording. To process and dispatch YL69 sensor data and DHT11 sensor, the Arduino UNO microcontroller is used as well as a relay as a switch to drain and disconnect the electric current to the water pump. The design results show that this automatic plant watering monitoring system can work well, where the soil moisture is below <50%, the water pump will live "ON" and if the soil moisture is above> 60% the water pump will die "OFF". From the results of the design and testing of the monitoring system carried out it is able to monitor data from the YL69 sensor, DHT11 sensor and pump conditions in real-time with the mobile application (Blynk). While the thingspeak web can monitor and record YL69 sensor data, DHT11 sensors and pump conditions every 20 seconds..

Drones and other unmanned aerial vehicles (UAVs) used for agriculture have recently emerged as a key tool for ground sensing in "smart farming." For precision agriculture's water management and monitoring and control systems, unmanned aerial vehicles (UAVs) are used as a mobile hotspot in areas without a dependable internet connection. In such places, the agricultural UAV equipped with a suite of Internet of Things sensors would be rendered ineffective. Currently, IoT sensors collect data on the soil's temperature and moisture and transmit that information to farmers through cloud storage and mobile apps rather than UAVs. In this proposed work, we have combined and connected UAVs and IoT network-based sensors. We have proposed a system to collect and measure the soil moisture contents remotely in real-time through a drone. For a country like India whose main source of revenue is agriculture, this domain is not sufficiently explored in terms of technology. The lack of sufficient research in this domain has been a problem for the livelihood of those farmers whose sole existence depends on agriculture. An economical process could be devised that could help automate the process of knowing the exact soil moisture content of the entire farmland. Farmers would benefit greatly from such a process. In this proposed work, we monitor real-time soil moisture by collecting the data using the soil moisture sensor and an Arduino UNO. The transmitted data is transmitted to the drone, which further sends the resultant data for real-time monitoring and analysis to the cloud.

The increasing demand for sustainable agricultural practices has led to the integration of IoT technology into farming. This paper presents the Smart Agro-Climate Advisory System, an IoT-based smart farming solution that monitors soil moisture, temperature, humidity, and motion detection while automating irrigation. The system is designed to enhance agricultural efficiency by reducing water wastage and providing real-time environmental insights to farmers. Utilizing NodeMCU ESP8266, Soil Moisture Sensor, PIR Motion Sensor, and a Relay Module, the system ensures efficient water management and security for crops. The Blynk IoT platform enables real-time data visualization, remote irrigation control, and security alerts through a mobile application. The automation of irrigation using real-time soil moisture data significantly minimizes water overuse while optimizing crop health. Additionally, the inclusion of a PIR motion sensor enhances security by detecting unauthorized movement within the field, alerting the farmer through the IoT platform. This research explores the system's architecture, implementation, and advantages, demonstrating how IoT-based solutions can revolutionize traditional farming methods. By leveraging cloud-based analytics and automation, the Smart Agro-Climate Advisory System provides an effective approach toward precision agriculture, water conservation, and smart farming, ultimately ensuring sustainable agricultural growth.

Smart irrigation systems play a crucial role in water management, particularly in urban greening applications aimed at mitigating urban heat islands and enhancing environmental sustainability. These systems rely on soil moisture sensors to optimize water usage, ensuring that irrigation is precisely tailored to plant needs. This study evaluates the performance of four commercially available capacitive soil moisture sensors-TEROS 10, SMT50, Scanntronik, and DFROBOT-across three different substrates under controlled laboratory conditions. A total of 380 measurements were conducted to assess sensor accuracy, reliability, and the influence of insertion technique on measurement variability. Results indicate that while all sensors adequately cover the moisture ranges critical for plant health, their accuracy varies significantly, highlighting the necessity of substrate-specific calibration. TEROS 10 exhibited the lowest relative deviation and highest measurement consistency, making it the most reliable among the tested sensors. DFROBOT, despite being the least expensive, performed comparably to SMT50 and Scanntronik in certain conditions. The findings provide valuable insights for selecting and calibrating soil moisture sensors in smart irrigation applications, ultimately contributing to improved water efficiency, plant vitality, and sustainable building-integrated greenery.

In India, given the rising trend of population growth, climate change and the need to increase agricultural production with efficient utilization of water, It is crucial to execute precise water management strategies in the farmland. In this study, efforts were made towards development of an automated system for irrigation scheduling on real-time basis considering the soil moisture conditions and crop parameters, and evaluation of performance under different irrigation methods in tomato crop. The soil moisture sensor was integrated with decision support system (DSS) and microcontroller using internet and global system for mobile communication (GSM) module for automated irrigation. The developed sensor was compared with Frequency Domain Reflectometer (FDR), tensiometer, and watermark sensor and was calibrated using the gravimetric method. The crop and irrigation water productivity of tomato crop ranged from 5.2–12.6 kg m-3 for control and automated systems, and 7.7–18.7 kg m-3 for the latter under different methods of irrigation. By using an automated drip irrigation system instead of a manually operated check basin irrigation system, cultivators of tomatoes were able to save 39.61% of the water. In terms of economics analysis, highest benefit cost ratio were obtained under manually operated drip irrigation (2.61) followed by automated drip irrigation system (2.50) in tomato crop.

Football is not only carried out as an ordinary sport, but the sporting achievement itself is an asset that can popularize a region or country. In the smooth running of sports activities, stadium facilities were established to support the success of playing soccer. During the rainy season, the match will be disrupted due to the fact that the football field has excessive water, which hinders the match. The system used today to control excessive water on the soccer field is by using an impregnation system. Therefore, a tool is needed that can help reduce excess water during heavy rains. So a prototype water control device was designed on a football field using a soil moisture sensor that can detect soil moisture, using a water pump assisted by a relay to reduce the presence of excess water, as well as using a servo to raise and lower the tools used to spray water and also suck up water. All of these design components are controlled by Arduino uno. This test process if the soil is in soil moisture < 45% then Arduino orders the tool to work because at that humidity the soil is dry. If the soil moisture is > 55%, the servo and also the relay are ordered to work because at that humidity the soil is wet

Here we have developed a new model to simulate supplemental irrigation and the hydro-economic potential of a rainwater harvesting system in rainfed agricultural areas. Using the model, soil moisture in rainfed crop land, supplemental irrigation requirements, rainwater storage in an on-farm reservoir (OFR) system, and surface and ground water availability were predicted. In an irrigated system, an OFR was used to harvest rainwater during the rainy season, and stored water was applied to cropland as supplemental irrigation (SI). An economic analysis was performed to calculate the benefits due to an OFR irrigation system, and gains from increased crop yield and downstream water availability in the irrigated OFR system were compared with rainfed system (i.e. no OFR). In addition, we calculated the impacts of dry and wet seasons on total value gains (grain and water gains) for irrigated and rainfed conditions and performed a sensitivity analysis to quantify the impacts of model input parameters on total value gains. Analyses showed that the OFR system can produce crop yields three times greater than rainfed agriculture. During a water stress season, the total water use in the irrigated system was 65 % greater than for the rainfed system. Water use efficiency of the irrigated system was 82 % higher than for the rainfed system. In a dry season, the total value gains due to increased crop yield by supplemental irrigation and downstream water availability of the irrigated system were 74 % greater than for the rainfed system, while in a wet season the total value gain of the irrigated system was 14 % greater than for the rainfed system. A precipitation scenario analysis of wet and dry seasons indicated that the benefits of a rainwater harvesting system can be considerably greater in dry seasons than wet seasons.

IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment

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.