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This study aims to design, implement, and test a prototype that automates three functions, namely watering, fertilizing, and pest control based on Arduino Uno with the ability to directly monitor soil moisture and pH. This system is equipped with four main types of sensors. Soil condition monitoring involves an FC-28 soil moisture sensor and a soil pH sensor, water level measurement involves an HC-SR04 ultrasonic sensor, and pest detection in the plant area involves a RIP sensor. All data obtained from these sensors is then processed by the Arduino Uno microcontroller to automatically activate actuators such as water pumps, liquid fertilizer pumps, buzzers, and DC motors according to soil conditions and plant needs. Prototype testing was conducted on simulated land with various scenarios of moisture, soil pH, and pest activity. The test results revealed that the system was proven to be able to significantly optimize water and fertilizer utilization, as well as reduce pest disturbances that could potentially damage plants.  In addition, this system also displays the operational status directly through an LCD screen, making it easy for users to monitor. The advantage of this system is its multi-function integration in a single device that is cost-effective and easy to operate. In the future, the functionality of this system can be improved through integration with Internet of Things (IoT) technology, enabling remote monitoring and control with greater efficiency. More broadly, this study is expected to support increased production and sustainable agricultural practices in Indonesia.

Fruit cultivation plays a crucial role in the agricultural economy, where seed quality significantly impacts productivity. Watering and fertilizing fruit plant seedlings are key aspects of ensuring healthy growth. To meet the demands of modern agriculture, an automated solution has been developed utilizing messaging application-based technology, such as Telegram. This device enables remote control of watering and fertilizing processes via the Telegram bot feature, ensuring precision and convenience. Advantages include time efficiency, optimal fertilization, and precise watering, supported by light sensors and soil moisture sensors to enhance the process. Experimental results show that this technology successfully addresses challenges related to irregular watering and fertilization. Consequently, this automated system has the potential to enhance productivity and efficiency in fruit cultivation.

In order for life to exist on Earth, water is required and is particularly important on ships. Concerns about water scarcity arise because water resources cannot always meet demand. pH has an impact on the quality of drinking water, with an ideal range between 6.5-8.5. Alkaline water with a pH of 8.8 has health benefits, including helping to lower stomach acid and improve body oxygenation. The pH of drinking water recommended by the EPA is between 6.5-8.5 to ensure safe consumption. pH is a measure of the acidity or basicity of water, on a scale of 0-14, where 7 is considered neutral. The research plans to make a drinking water pH control system using an ESP 32 microcontroller. This research aims to control also monitor the pH of drinking water efficiently using ESP 32 microcontroller. This research uses the Research and Development (R&D) method to design pH control in drinking water solutions. The phases of the research include using a pH sensor to detect pH values, using an ESP 32 microcontroller to control pH, and validating and improving the product model. Overall system testing in the design of a drinking water pH controller system from water treatment is an important stage to ensure successful integration between all components and desired functionality. This testing process includes several main stages, Hardware Integration Testing: All hardware is physically connected and integrated, including ESP32, relays, solenoid valves, and pH sensors. This test is taken to ensure that all components are properly installed and interact with each other correctly. Software Integration Testing: This type of testing verifies that all features and functions of the system function as intended by the software program responsible for it. This includes testing Wi-Fi connections, integration with the Blynk platform, and programming logic as an automatic water controller. Testing System Functionality: to ensure that the intended features can be run properly, the system is tested in various usage scenarios. This includes testing the water controller automatically. the designed system can function normally and adjust appropriately to the designed controller system. From the data obtained regarding the performance results of the system built, it was found that the pH controller system can be run automatically based on the water that has been set as the set point of the system created. The monitoring system with IoT is also able to run well. The time needed will be more to control the pH in the range of 6.5-8.5.

Sea water pollution is an increasingly urgent global issue, caused by various factors such as industrial waste, household waste, and ship activities. One of the solutions needed to overcome this pollution is the development of a detection system that is able to monitor polluting substances quickly, accurately, and efficiently. This research aims to design and build a microcontroller-based seawater pollution detection system, which can identify various pollution parameters in real-time. This research uses the Research and Development (R&D) method to develop a system consisting of several main components, including a pH sensor, turbidity sensor, Arduino Uno, GPS module, Raspberry Pi 4, USB camera, LiPo battery, and step-down converter. Each component is tested individually before being integrated into the overall system. The results of testing in a real environment show that the system is able to detect seawater pollution parameters with high accuracy. However, there are some errors in data collection, especially in the camera sensor with a percentage error of 32%, turbidity sensor 20%, and pH sensor 24%. Further improvements and developments were made based on the evaluation results to enhance system performance. The resulting system is considered accurate, reliable and easy to use, making an important contribution to efforts to protect seawater quality and mitigate the negative impacts of pollution on the environment and human health.

Ships as an important means of transportation require the availability of good quality fresh water to meet the daily needs of the crew. Because the quality of fresh water that does not meet the standards can interfere with the activities of the crew. This research aims to build a water treatment system on board controlled by ATMEGA 2560 microcontroller. The system is equipped with turbidity sensor SEN0189, TDS sensor SEN0244, and PH sensor SEN0161 to monitor the freshwater quality. The process of working this tool by treating fresh water which then the parameters are detected by the PH sensor, TDS sensor, and turbidity sensor which then the detection results are displayed on the LCD monitor, and the buzzer and LED turn on when the condition of the fresh water parameters does not meet the standards. The methodology and design of this system will be carried out with experimental research methods where in this method at least one variable is manipulated to study the cause-and-effect relationship. The results of testing water treatment using ATMEGA 2560 show that the system can work optimally in treating fresh water. And the accuracy of the PH sensor, TDS sensor, and turbidity sensor is quite accurate with the difference in error with the comparison measuring instrument less than 5%.

The decline in water quality is a serious environmental issue, particularly in urban areas. This research aims to develop an Internet of Things (IoT)-based water quality monitoring system using ESP32, pH, TDS, and turbidity sensors. The system is designed to monitor water quality parameters in real-time and transmit data to a cloud platform for further analysis. The system prototype was tested with water samples from various sources, and the results demonstrated high accuracy, with a maximum deviation of ±0.5% compared to laboratory results. Thus, this system offers an efficient and easy-to-implement solution for continuous water quality monitoring, which can aid in water resource management in urban environments.

In the hold of the fishing boat, it is currently unable to control the pH of the water in accordance with the living environment of the fish. The pH of the water also needs to be considered so that the fish can survive. In addition, fish feeding on fishing vessels is also very necessary. The purpose of this research is to design a system that can control pH, fish feeding, fish water replacement. in the fish hold using an IoT-based microcontroller. The method used in this research uses quantitative methods through system design, design software design models, product trials.This method is used This research method includes steps taken to design and implement the system, as well as tests carried out to ensure the performance and success of the designed system. The results of the data designed by the system are analyzing the data in testing this tool according to its function. The accuracy of using the tool when feeding is 90.5% and the percentage error is 9.5%. The accuracy of using the tool when draining mode is 100% with a percentage error of 0%. And for the results of the percentage error of the pH sensor when the mode is on by 100% with a percentage error of 0%. This shows that the Smart Pond system designed has a high level of accuracy in terms of fish feeding and pond draining.

Hydroponics are now increasingly in demand, should be checked regularly so that hydroponic plants thrive. Likewise, in Siliwangi Indah Hydroponics Semarang, which still uses manual methods, namely the absence of a device that detects nutrient water temperature and pH automatically and the absence of tools that can normalize nutrients automatically. Arduino Uno R3 can be used to detect temperature automatically with a temperature sensor DS18B20, and detect pH with a pH sensor. Then the sensor readings are sent to the farmer's cellphone with SMS Gateway. The sensor readings are also used to divert the flow of nutrients from the spare reservoir, so that the nutrients remain normal. So this tool can automatically measure the nutrient water temperature and pH and replace the main nutrients to the reserve nutrients. And the assessment obtained from experts on this tool gets a value of 3.6 and from the expert gets a value of 3.7. Hydroponic nutrition in this study is maintained normally and farmers always know the nutritional state. So that the hydroponic plants thrive and have maximum yields.