Smart Iraqi Farms Based on Internet of Thing

Abstract

The concept of smart agriculture in Iraq includes innovative methods of farming that integrate technology and sustainable practices to enhance agricultural productivity and efficiency. By adopting techniques such as using water-efficient irrigation systems and conserving resources, Iraq can address the challenges associated with climate change and water scarcity in agriculture. Therefore, the topic of smart agriculture in Iraq, based on the Internet of Things, was adopted in this dissertation . was divided into 3 stages : 1- In this stage, the following sensors were used (NPK1, NPK2, NPK3) to measure the basic soil elements nitrogen, phosphorus, and potassium. The following sensors (X1, X2) were also used to measure PH, soil temperature, and conductivity.  This is for the sample that was irrigation intelligently and the data was collected in the form of a quantitative Excel file, and the total of record in system of 5 sensors (4823) record. In this system, several measurements were taken for nitrogen, phosphorus, potassium, PH, soil temperature, and conductivity, and then the average readings were taken to calculate the final value for each of the factors.2- In this stage, the sensors (NPK4, NPK5) were used to measure the following parameters: potassium, nitrogen, and phosphorus. Other sensors (X3, X4) were also used to measure other parameters as well, such as conductivity and PH. And the total of records in system of 4 sensor (2991) record. The data collected from the above sensors was used as the data set that will be used in comparison with the smart system (5 sensors). Also, the irrigation process here used traditional irrigation, which had a negative impact on agricultural production, as we saw in the results of the data analysis. Compared to using the smart irrigation method, which had a positive effect on the product as well as on mineral soil elements such as nitrogen and potassium. Also The C programming language was used to program the Arduino. 3- In this stage, the smart irrigation system, the result was reached that the amount of water used was saved approximately 60%, and this was calculated through the mathematical calculation of the sample used. This indicates the difference in saving water between using smart methods of irrigation and traditional methods of irrigation. Also, the smart irrigation process preserves the soil, increases the product, and also preserves the mineral components of the soil. The irrigation process is carried out quantitatively by reading from the soil moisture sensor, and when the moisture reaches 200 or less, the smart valve is opened. Otherwise closed and, the sensor will read again. Note that the readers are programmed every 24 hours, and this number depends on the type of the plant and the season, whether summer or winter. After that, the water is turned on for 10 minutes according to the programming for the sample. This can be changed according to the need , sample and the type of plant . And This procedures implemented in Arduino IDE language . To evaluate the data and determine if the soil was appropriate for agriculture or not, four algorithms (machine learning algorithms) were used: decision trees, random forests, support vector machines, and KNN. In order to implement these methods, the Python programming language was utilized