Development of IoT Based Smart Irrigation System with Programmable Logic Controller

Smart irrigation system is an automatic irrigation and monitoring system on agricultural land with a sensor, automation, and control technology based on the Internet of Things (IoT). This system can reduce the agricultural activities that were previously performed manually into an automatic system with a reduced human supervision. Smart Irrigation systems that are widely developed used Arduino as the controller. Arduino still lacks in response, low durability, and sensitivity to temperature change, hence requiring frequent maintenance to avoid weather disturbances, insects, and others. This paper presents a development of a smart irrigation system using a Programmable Logic Controller (PLC) as the controller and a soil moisture sensor as a humidity condition measurement tool. The advantage of using PLC as a controller is more stable and has sensor compatibility with higher accuracy. Hence the results are more consistent and accurate. The PLC system is expandable, allowing for the inclusion of more channels for sensors and other measurement instruments. The developed system can collect data on soil moisture conditions, trigger valves, and perform auto irrigation using sprinklers, reducing or even eliminating the need for human intervention. The IoT collects data from sensors and updates the data into a database system, allowing users to monitor the land conditions in real-time. The developed system was predicted to save manpower (20%) and water usage (42.47%) compared to the conventional method. Keywords: Smart Irrigation; IoT; PLC; Moisture Sensor; Sprinkle

Evaluation of Smart Irrigation Controllers: Year 2011 Results

A smart controller testing facility was established by the Irrigation Technology Center at Texas A&M University in College Station in 2008 in order to evaluate their performance from an "enduser" point of view. The "end-user" is considered to be the landscape or irrigation professional (such as a Licensed Irrigator in Texas) installing the controller. Controllers are tested using the Texas Virtual Landscape which is composed of 6 different zones with varying plant materials, soil types and depths, and precipitation rates. This report summaries the results from the 2011 evaluations. Nine controllers were evaluated over a 152 day period, from April 11 - May 29, 2011 and August 8 to November 20, 2011. Controller performance was analyzed for each seasonal period (spring, summer, fall). Controller performance is evaluated by comparison to the irrigation recommendation of the TexasET Network and Website, as well as for irrigation adequacy in order to identify controllers which apply excessive and inadequate amounts of water

Aplikasi Irigasi Cerdas di P4S Buana Lestari, Kabupaten Nganjuk, Jawa Timur

This activity aims to conduct trials and make pilots of one form of smart irrigation application in melon cultivation with a hydroponic system, as well as to increase farmers' knowledge in managing irrigation schedules. The expected outcome is increased irrigation efficiency, productivity of irrigation water, and farm income. The technology used in this activity is an IoT-based smart irrigation system. The smart irrigation system used consists of a soil moisture sensor that will detect the wetness of the soil, planted at a depth according to the irrigation technical needs. Information from the sensors will be entered into a programmable controller that has an Internet of Things (IoT) function with a wireless connection to a cloud server. The measurement results of the EU value on the installed drip irrigation network are classified as high, which ranges from 81.55% – 83.24%. This means that wherever the position of the sensor is installed, it will relatively represent (actual) the condition of the water content of the planting medium in the field. The application of smart irrigation can increase the efficiency of drip irrigation in melon cultivation with a hydroponic system, namely saving nutrient water by 6,500 mL per plant, or 7.64% or the equivalent of Rp183,00/melon plant. With smart irrigation applications, the productivity of irrigation water and nutrition is 20 grams of melon per 1 L of irrigation water. The trial of this smart irrigation application needs to be continued with an "on-demand" irrigation scheduling system, to obtain the highest irrigation efficiency and water productivity.Kegiatan ini bertujuan untuk melakukan uji coba dan membuat percontohan salah satu bentuk aplikasi irigasi cerdas pada budidaya tanaman melon dengan sistem hidroponik, serta untuk meningkatkan pengetahuan petani dalam mengatur jadwal irigasi. Hasil yang diharapkan adalah meningkatnya efisiensi irigasi, produktivitas air irigasi, dan pendapatan usaha tani. Teknologi yang digunakan dalam kegiatan ini adalah sistem irigasi cerdas berbasis IoT. Sistem irigasi cerdas yang digunakan terdiri dari sensor kelembapan tanah yang akan mendeteksi tingkat kebasahan tanah, ditanam pada kedalaman sesuai kebutuhan teknis irigasi. Informasi dari sensor akan dimasukkan ke programmable controller yang memiliki fungsi Internet of Things (IoT) dengan koneksi nirkabel ke cloud server. Hasil pengukuran nilai EU pada jaringan irigasi tetes terpasang tergolong tinggi, yaitu berkisar antara 81,55% – 83,24 %. Hal ini berarti bahwa dimanapun posisi pemasangan sensor, akan secara relatif mewakili kondisi kadar air media tanam aktual di lapangan. Aplikasi irigasi cerdas dapat meningkatkan efisiensi irigasi tetes pada budidaya melon dengan sistem hidroponik, yaitu penghematan air nutrisi sebesar 6.500 mL per tanaman atau sebesar 7,64%, setara dengan Rp183,00/tanaman melon. Dengan aplikasi irigasi cerdas, produktivitas air irigasi dan nutrisi sebesar 20 g melon per 1 L air irigasi. Uji coba aplikasi irigasi cerdas ini perlu dilanjutkan dengan sistem penjadwalan irigasi on-demand, untuk memperoleh efisiensi irigasi dan produktivitas air tertinggi

Smart Surge Irrigation Using Microcontroller Based Embedded Systems and Internet of Things

Surge Irrigation is a type of furrow irrigation and one of many efficient irrigation techniques. It is one of the economical techniques and requires minimum labor for monitoring it. In surge irrigation, water is applied intermittently to a field to achieve uniform distribution of water along the furrows, which is important while irrigating, as it ensures that there is enough water near the root zone of the crop. The uneven distribution can cause a loss in crop productivity. Surge irrigation uses a surge valve, which is an electro-mechanical device that irrigates a field. The commercial surge valves available on the market are made to control only the time for the irrigation. However, their functionality is limited and requires human intervention to control and monitor the irrigation process. Therefore, monitoring the irrigation with these controllers is a big challenge. The lack of monitoring may result reduced irrigation efficiency. The purpose of this thesis is to design and develop an embedded system for surge irrigation that resolves the drawback associated with the commercial surge valves. In this thesis, a “Surge Controller” is designed, implemented, and tested on the farm. The surge controller is a microcontroller-based embedded system, which runs the real-time operating system FreeRTOS on a single core ARM Cortex M3 microcontroller for multitasking. The important feature, which makes the surge controller “Smart”, is the Internet of Things (IoT) that enables the controller to send irrigation data over the Internet to a remote station. During the Spring and Summer, 2017, the surge controller was developed and tested in the field at Rice Research and Extension Center of the University of Arkansas. Five irrigation events were run in a 20 acres soybean field. The controller was tested for the durability of the components in the environment and field conditions, performance and overall feasibility of the device to achieve successful results from an irrigation event. After the successful testing, the IoT feature was added in Fall 2017 and Spring 2018 and tested for its functionality by running a few irrigation events in the Laboratory. The surge controller worked as expected continuously without interruption

Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy

Decision support for optimised irrigation scheduling

The system, developed under the FLOW-AID (an FP6 project), is a farm level water management system of special value in situations where the water availability and quality is limited. This market-ready precision irrigation management system features new models, hardware and software. The hardware platform delivers a maintenance-free low cost dielectric tensiometer and several low-end irrigation or fertigation controllers for serving different situations. The software includes a complete, web based, Decision Support System (DSS) that consists of an expert planner for farm zoning (MOPECO) and a universal irrigation scheduler, based on crop-water stress models (UNIPI) and water and nutrient uptake calculations. The system, designed also to service greenhouse fertigation and hydroponics, is scalable from one to many zones. It consists of 1) a data gathering tool which uploads agronomic data, from monitored crops around the world, to a central web Data Base (DB), and 2) a web based Decision Support System (DSS). The DSS processes intelligently the data of the crop using Crop Response Models, Nutrient Uptake Models and Water Uptake Models. The central system returns over Internet to the low-end controller a command file containing water scheduling and nutrient supply guideline

Smart irrigation control using inexpensive capacitance probes

The mass marketing of inexpensive capacitance probes has opened the door for development of smart irrigation controllers based on soil moisture content. The advantage over climate based irrigation is that these systems are easier to use and can compensate for rainfall and variations in the irrigation system application rate. In this work, a smart irrigation controller was developed using EC-5 Echo sensors connected to Siemens LOGO microcontrollers to start the irrigation process. The system was validated in a lettuce crop grown in a greenhouse in southern Portugal. The sensors were buried 10 cm in the center of mini-lysimeters with four different trigger points: 25, 22, 20 and 17% volumetric soil moisture, and the irrigation depth set to replenish the soil to field capacity. The results indicate that the main challenge to soil irrigation control is the precise location of the sensor in relation to the drippers. In this work no significant differences in crop yield were observed between the three treatments, although there was a water economy of some 5% when using the lower trigger point, possibly due to smaller losses from soil evaporation

Human-in-the-Loop Model Predictive Control of an Irrigation Canal

Until now, advanced model-based control techniques have been predominantly employed to control problems that are relatively straightforward to model. Many systems with complex dynamics or containing sophisticated sensing and actuation elements can be controlled if the corresponding mathematical models are available, even if there is uncertainty in this information. Consequently, the application of model-based control strategies has flourished in numerous areas, including industrial applications [1]-[3].Junta de Andalucía P11-TEP-812