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Conventional vegetable watering often presents challenges, particularly in ensuring that plants receive adequate water without excessive manual intervention. This research proposes a solution in the form of an automatic watering system using fuzzy logic, which integrates soil moisture sensors, rain sensors, and an RTC (Real-Time Clock) for scheduling. The system is designed to replace manual watering methods with an automated process, thus improving the efficiency and effectiveness of vegetable cultivation. The developed device uses a soil moisture sensor to monitor soil conditions, a rain sensor to detect rainfall, and an RTC to determine the optimal watering times. The Arduino Uno acts as the main controller that activates the water pump via a relay driver based on data received from the sensors. Test results show that the system operates according to the established criteria, with a satisfactory accuracy level. The system successfully waters the plants at 07:00 WIB and 15:00 WIB, based on dry soil conditions and no rain. The trials showed that the device has an average soil moisture measurement error of 5%, and a time discrepancy of about 22 seconds on the RTC module. Each 1% increase in soil moisture requires approximately 1 second of watering duration. Watering times are adjusted to prevent the plants from drying out or dying, with a soil moisture threshold of below 40% set as the condition for requiring watering.

The soil moisture sensor provides numerical measurements to detect changes in soil moisture using an analog voltage output. This research aims to develop a capacitive sensor based on a statistical model to detect soil moisture for plant watering, leveraging the Internet of Things (IoT). The analysis was conducted using polynomial and linear regression models. The modeling process was based on primary gravimetric test results from dried soil. The best model coefficients, selected based on the highest adjusted R-squared value, were used for sensor recalibration. A watering system was then developed using an Arduino and a model-driven capacitive soil moisture sensor integrated into an internet-connected smart plant pot, enabling remote control via a mobile phone. The research findings indicate that the 8th-order polynomial model, with the highest adjusted R-squared value of 0.9583, is the most accurate. The smart watering system using the model-driven capacitive sensor achieved soil moisture prediction outcomes ranging from 0.08 to 1.01 for 150 to 418 sensor data points. The internet-connected smart plant pot allows precise and real-time control, delivering notifications and enabling actions when plants require watering.

Low-cost automatic irrigation systems require quality calibrated soil moisture sensors. The sensor is an indirect method of soil moisture measurement. The sensor works based on the change in the dielectric constant. So, it requires to be calibrated in terms of the soil water content. Polynomial and linear models are frequently used to calibrate soil moisture sensor data in the gravimetric test method. However, computational effort is required. This study aims to obtain a sensor calibration application that can provide the best model of the available models for model-based capacitive soil moisture sensor. This research was conducted using primary data from gravimetric test experiment on Internet of things (IoT) based soil moisture sensor. Web-based re-calibration application produced best model based on adjusted R Squared. Finally, model-based capacitive soil moisture sensor set up using best model coefficient. The results show that the web-based re-calibration application can provide the best model for model-based capacitive soil moisture sensor. Based on gravimetric test experiments and web applications, the best model is a polynomial regression model order 3 with 0.945 adjusted R Squared. The model predicted value for soil moisture is in the range 0 – 1.2 for raw sensor data values of 100 – 530. When the model coefficient configured in capacitive soil moisture sensor and Blynk application, soil moisture measurement can be done via mobile phone in real time.

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The process of manual fertilization and irrigation of plants has disadvantages such as it requires human labor and is inefficient in the use of fertilizers and water sources. Therefore, the purpose of this research is to design and develop an automatic fertigation system. The method used in this research is a drip fertigation technique where the fertigation liquid that has been stirred is placed in a tank with 100 cm height from ground. With the gravitational force, the fertigation liquid is distributed through pipes, hoses and emitters around the plant. While the control system and automation of fertigation distribution to plants is carried out based on a microcontroller that need the condition of soil moisture values around the plant. If the watering time and humidity values are met, the electronic valve will open so that the fertigation liquid flows from the tank to the plants. Furthermore, in this study the tests were carried out to determine the uniformity coefficient and debit of drip fertigation. From the results, it shows that the emitter’s debit influenced by the liquid level in the tank. The uniformity coefficient obtained in the two tests is greater than 90%. From the two tests carried out from the moisture sensor 1 and 2, it shows the mean percentage error for both sensor is less than 1.7%, while the percentage error of soil moisture sensor 1 is 1.6% and the percentage error of soil moisture sensor 2 is 1%, respectively. Meanwhile, from the ultrasonic sensor testing it was obtained 0% of error. It also shows from the testing conducted that the fertigation system works very well and successfully.

Eucheuma cottonii is a type of seaweed that is cultivated in the coastal area of Nagari Sungai Pinang, Koto XI Tarusan District, Pesisir Selatan District, West Sumatra Province. Before being sold, seaweed farmers must dry their seaweed first, because what can be sold is dried seaweed. Drying the seaweed takes two to three days depending on the weather conditions. In this research a seaweed drying system has been designed with a tool that rotates the seaweed in the drying chamber. In this rotary drying system, the soil moisture sensor is used which functions to detect the moisture content of the seaweed, if the moisture content of the seaweed is still read > 30% then the microcontroller turns on the relay which forwards instructions to the heater and the DC motor starts rotating the player container. The DS18B20 sensor is used to detect the temperature of the drying chamber, if the total moisture content of the seaweed is 30%, then the state of dry seaweed has been reached. Tests have been carried out to determine the difference in time required between the seaweed drying process using the system that has been built in this study and the seaweed drying process that utilizes direct sunlight. To achieve a moisture content of 30% in the seaweed drying process with the system designed in this study it takes an average of ±50 minutes, while using direct sunlight it takes ±9 hours to dry the seaweed.

Tanaman merupakan tumbuhan yang dibudidayakan agar dapat diambil manfaatnya oleh sebab itu memerlukan perawatan yang intensif berupa penyiraman dan pemupukan yang teratur sesuai dengan resistensi media tanam dan karakteristik dari tanaman. Diberbagai daerah petani masih melakukan penyiraman dan pemupukan secara manual cara tersebut kurang efektif karena debit air tidak sesuai dengan kebutuhan dan menghabiskan tenaga dan waktu yang cukup lama. Maka dari itu petani untuk segera beralih ke system otomatisasi penyiraman dan pemberian pupuk cair pada tanaman. Pemberian air dan pupuk pada tanaman secara otomatis yang dikendalikan oleh mikrokontroller arduino sebagai pusat kontrol dan beberapa komponen sebagai alat pendukung dari sistem otomatis berdasarkan data hasil pengukuran menjadi solusi untuk meringankan pekerjaan dan meningkatkan produktivitas tanaman. System otomatis bekerja berdasarkan informasi beberapa sensor mengenai kondisi tanah pada tanaman dengan pengontrolan mikrokontroller arduino. Penyiraman tanaman dilakukan ketika sensor soil moisture membaca kelembaban tanah sesuai dengan set point yang telah ditentukan yaitu pada range >700, dan penyiraman akan berhenti ketika tanah pada tanaman dalam keadaan basah dan sesuai dengan set point yang telah ditentukan pada range >650. Dan untuk pemberian pupuk cair pada tanaman menggunakan RTC yang berfungsi sebagai penjadwalan pemberian pupuk cair yang terlebih dahulu dilakukan setting hari dan waktu pada program sesuai dengan set point yang telah dilakukan.

The problem of stabilizing soil moisture can be addressed by designing a soil moisture control application that serves to provide information on soil moisture conditions within a certain time period in the form of an order to water and stop watering. The research aims to carry out a sensing simulation on Soil Moisture Control Application in Smart Garden using Soil Moisture Sensor. This research is an experimental research of tool design in order to improve the quality and working system of the tool. The results of this study indicate that the device will function or not If the sensor detects that the ground is dry or the measurement results are brought to 50%, then the sensor will respond and send a signal to the microcontroller to activate the relay so that the pump will turn on automatically. If the device does not function then we can do it automatically manually by controlling it via a smartphone application. When the soil reaches a soil moisture level above 50% from the results of either watering done by the tool or from the rain detected by the soil mousture sensor then the tool will stop automatically and the tool will return to function when the soil returns dry, so that it can control soil moisture. This tool is equipped with indicators using LED lights when the tool is functioning.