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The quality of boiler feedwater is a crucial factor in maintaining the operational reliability of ship machinery systems against the risks of corrosion and scale formation. This research focuses on the design and development of a real-time monitoring system based on the Internet of Things (IoT) to automatically determine water quality. The hardware development utilizes a NodeMCU ESP32 microcontroller that integrates four main sensors: a pH sensor, a DS18B20 temperature sensor, a Total Dissolved Solids (TDS) sensor, and a turbidity sensor. The methodology applied is an experimental systems engineering model, encompassing circuit design, software programming, and the implementation of simple artificial intelligence. The automatic decision-making process in this tool is designed using zero-order Sugeno fuzzy logic with input parameters of turbidity, salinity, and acidity level (pH). The obtained data is transmitted wirelessly to a Firebase database and visualized through a 0.96-inch OLED display. Functional tests on seven fluid characteristics including pure water, hard water, and muddy water show that this prototype can accurately classify water quality into Good, Fair, and Poor categories. The main contribution of this design is the provision of a preventive, efficient, and applicable boiler maintenance solution for the modern shipping industry.

Sea Surface Temperature (SST) is an important parameter in oceanographic studies because it influences climate dynamics, ocean circulation, and marine ecosystems. Continuous monitoring of SST in open sea areas requires a reliable system capable of operating autonomously. This study develops a solar-powered ocean buoy designed to measure sea surface temperature while simultaneously evaluating the performance of a solar panel as the main energy source. The system uses a DS18B20 sensor to measure SST and an INA219 sensor to monitor the voltage, current, and power of the solar panel, while an ESP32 microcontroller functions as the central data processing unit. The results show that sea surface temperature tends to remain relatively stable with small daily variations, whereas the temperature and performance of the solar panel exhibit larger fluctuations due to direct exposure to solar radiation and changing weather conditions. Solar panel performance also shows significant variations in current and power depending on the intensity of sunlight. To analyze the influence of SST variations on solar panel performance, a statistical analysis using Analysis of Variance (ANOVA) was conducted. The ANOVA results, based on the calculated F-value and the significance value (p-value) at a confidence level of α = 0.05, indicate that SST variations have a significant effect on solar panel performance, demonstrating that the proposed solar-powered buoy system can operate autonomously and has potential for long-term SST monitoring in offshore areas.

Catfish farming is one of the fisheries areas with great potential in Indonesia. However, the problem of feed efficiency, use of probiotics, and air temperature control are still the main obstacles that affect the health and growth of fish. This study aims to design and implement an automatic system that can regulate the provision of feed and probiotics and control and control air temperature directly using the ESP32 microcontroller. This system has several important components, such as the ESP32 microcontroller as a control center, servo motors for feed and probiotic distribution, and DS18B20 temperature sensors to monitor air temperature. All components can be controlled and viewed through an IoT-based application with a Wi-Fi connection or applications such as Telegram. This trial aims to determine whether this system can provide feed and probiotics according to the specified time, and maintain air temperature in the optimal range (28°C–40°C) for catfish growth. In this way, the system is expected to increase efficiency in catfish farming automatically, reduce the need for human labor, and minimize errors in pond management.

Energy efficiency in water heaters is a crucial factor in ship operational environments due to limited electricity resources that rely on generators. This study aims to design and build an IoT-based water heater monitoring system with an innovative heat storage medium in the form of a mixture of silica sand and paraffin wax to improve thermal efficiency. Although previous studies have developed temperature monitoring and control systems in IoT-based water heaters, this study specifically fills this gap by analyzing the performance of adding silica sand to overcome the low thermal conductivity of paraffin wax. Using the Research and Development (R&D) method, this system was built with an ESP32 microcontroller as the control center, a DS18B20 temperature sensor for accurate measurements, and the Blynk and Google Sheets platforms for real-time monitoring and data recording. Performance testing was conducted by comparing the water heating rate between pure paraffin wax media and the mixed media. The results showed that the monitoring system functioned reliably, and the main finding proved that the addition of silica sand to paraffin wax significantly increased heating efficiency. This was clearly seen from the reduction in time required to raise the water temperature to 40°C, from 2.5 hours to only 1 hour in the second heating cycle. The results of this study indicate that the integration of silica sand and paraffin wax media with IoT technology can increase the efficiency of water heaters and provide an innovative solution for energy-efficient and environmentally friendly temperature control.

Penelitian ini mengembangkan sistem pemantauan berbasis Internet of Things (IoT) untuk mengoptimalkan kinerja Mini PC dan pemeliharaan real-time di CV Permata Gemilang Jaya. Metodologi waterfall diterapkan menggunakanNodeMCU sebagai mikrokontroler utama, dilengkapi dengan sensor DHT22, DS18B20, dan INA219 untuk memantau parameter suhu, CPU, dan memori. Arsitektur sistem mengintegrasikan kerangka kerja Laravel dengan database MySQL, menghasilkan aplikasi web responsif dengan kontrol akses berbasisperan untuk Admin Pusat, Admin Regional, dan Teknisi Cabang. Infrastrukturserver cloud dengan konektivitas GSM cadangan memfasilitasi pemantauanterpusat di wilayah Ciayumajakuning. Desain sistem menggunakan Unified Modeling Language (UML) dengan diagram kasus penggunaan dan diagram aktivitas yang komprehensif. Penerapan sistem pemberitahuan otomatisdengan mekanisme peringatan berbasis ambang batas memungkinkan deteksidini anomali perangkat. Antarmuka yang dioptimalkan untuk selulermeningkatkan aksesibilitas teknisi untuk operasi lapangan. Validasi sistemmenunjukkan strategi pemeliharaan preventif yang sukses dalam mengurangiwaktu henti perangkat dan mengoptimalkan efisiensi operasional infrastrukturteknologi informasi.

Blood transfusion is a critical medical procedure that requires the blood to be at a temperature close to normal human body temperature, approximately 36– 38°C. Transfusing cold blood can lead to serious complications such as hypothermia, coagulation disorders, and even cardiac arrest. Therefore, a reliable and automated blood warming device is essential to ensure safe transfusions. This study aims to design and modify a Blood Warmer Thawing device based on the Arduino Uno microcontroller as an innovative and cost- effective solution, particularly for healthcare facilities with limited resources. The system integrates a DS18B20 temperature sensor to monitor the temperature of the heating medium in real time, with data displayed on a 20x4 I2C LCD. Users can set the desired temperature via a 4x4 keypad, and the system automatically adjusts the heater performance based on the detected temperature. To enhance safety and operational efficiency, the device is also equipped with a buzzer as a warning indicator when the temperature exceeds the safe threshold, and utilizes a DC motor and cooling fan to maintain proper heat circulation. Test results indicate that the device is capable of maintaining the liquid temperature within the ideal range for blood transfusions, with high stability and fast response to temperature changes. This innovation offers a practical, affordable, and easy-to-implement solution to support effective and safe blood transfusion procedures in various healthcare settings.

Technological advancements, particularly in microcontrollers and the Internet of Things (IoT), have brought significant changes to various aspects of life. Microcontrollers such as the ESP32, DS18B20 sensor, water pH sensor, and other supporting sensors enable the development of efficient automation systems. This research addresses issues related to the design and development of IoT devices for water quality monitoring, as well as the integration of these devices with web-based systems. The objective is to develop a device capable of monitoring water quality parameters such as pH, temperature, turbidity, dissolved materials, salinity projection, and dissolved oxygen projection, while providing automatic notifications under certain conditions. The development process applies the Agile methodology, which allows for rapid and adaptive iterations. Theoretically, this study contributes to improving understanding of IoT implementation and information systems, while practically, it provides a technological solution to support Koi fish farmers in monitoring and managing pond water quality. The expected outcome is a web-based water quality monitoring and management device for Koi ponds that can deliver real-time information and condition notifications, thereby reducing aquaculture risks and improving productivity.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring. 

A Baby incubator is one of the right instruments to overcome problems in handling newborn babies. An important parameter to control is the temperature of the baby incubator room. A study has been conducted on the Design of Baby Incubator Temperature Control with a PID System using a DHT22 sensor for the incubator room temperature sensor and a DS18B20 sensor for the baby's skin sensor. The microcontroller used is ATmega328. The temperature is maintained at 36 °C.  There is a heater component to heat the Baby Incubator if the temperature is >36 °C, a blower as a cooler if the temperature is <36 °C.  The temperature condition is displayed on the Nextion 4.3" LCD in real time using touchscreen technology. After being compared with the Incubator Analyzer, the overshoot value on the Incubator Analyzer was 0.74% while on the device made it was 0.20%. While the error value on the Incubator Analyzer was 0.02%, on the device made it was 0.01%. So it can be concluded that the tool operates properly according to what was planed.

The knee is the largest joint in the human body. Like other joints, the knee consists of several structures, such as muscle cartilage, ligaments, tendons, and nerves. Almost all leg movements depend on the knee joint. Therefore, the Knee Brace or Health Knee Brace is a tool designed to provide stability support and reduce knee pain. The purpose of this study was to design and build an Arduino-based knee pain therapy tool and to test the safety and effectiveness of the tool in reducing knee pain. This tool is designed using Arduino Mega as a microcontroller, using a DS18b20 sensor that functions as a temperature reader on the Knee support which has a heater pad as a heat generator, a Vibration Motor as a vibration effect giver on the tool and a 2.4 TFT LCD Touch Screen as a display and a 12V adapter on this tool. According to the analysis of the tool made by the researcher, based on the results of the function and performance tests, the Arduino-based Knee Pain Therapy tool can function properly and safely.

Sinusitis is a health disorder commonly caused by factors such as air pollution, dust exposure, cold air, and smoking. With the rapid development of technology, there are now healing methods that do not rely on conventional medications, such as laser therapy. This research aims to develop a laser therapy clock equipped with sinusitis therapy using Low-Level Laser Therapy (LLLT). The system utilizes Arduino Nano as the main controller, an IR laser for the nose and hand, a DS18B20 temperature sensor to monitor the patient's temperature, and an OLED 0.96V display to show laser intensity and temperature values. This system aims to improve patient interaction with the device, providing a convenient and effective way to perform sinusitis therapy at home. The goal is to create a non-invasive, user-friendly solution for individuals suffering from sinusitis, with the potential to enhance treatment effectiveness, accessibility, and convenience, offering a promising alternative to traditional treatments.

Technological developments in the agricultural sector, especially in the hydroponic method, provide solutions for optimizing plant growth in urban environments. This research integrates ESP32 microcontroller technology with a DS18B20 temperature sensor and TDS sensor to monitor and control temperature and nutrient quality in a hydroponic system. In addition, the Sugeno fuzzy logic method is used for automatic water quality monitoring.

This research focuses on developing an IoT-based automatic irrigation control system for stevia plants to optimize plant growth and water usage efficiency. The system integrates ESP32 microcontroller with soil moisture sensors, DS18B20 temperature sensors, and DHT11 environmental sensors for comprehensive monitoring. Using Research and Development (R&D) methodology with an experimental approach, the system was designed and implemented to automatically control irrigation based on soil moisture levels. The results demonstrate that the system successfully maintains optimal soil moisture by activating the pump when moisture levels fall below 38% and deactivating it above 40%. Real-time monitoring through the Blynk platform enables remote observation and control of environmental parameters. The integration of multiple sensors with IoT technology provides an efficient solution for stevia plant irrigation management, offering potential applications in smart agriculture.

Freon is one of the refrigerants used in refrigeration systems. The refrigeration system has a very important role, namely to preserve food ingredients so that food can last longer. The use of freon is not only used in ships but is widely found in home appliances in refrigeration systems used in freezers, air conditioners, refrigerators, and dispensers. If more freon is used, the negative impact that arises is greater, namely the depletion of the ozone layer and global warming which can have a bad influence on health, the life of living things and the environment. The purpose of this researcher is to create a tool to reduce the negative impact of freon use, namely by using peltier as a cooling medium with environmentally friendly thermoelectric modules. This study uses trial and error methods. Where the trial process is carried out by turning on one of the working push buttons and observing the temperature value. Then it is processed by the control system, namely Arduino Mega which will later provide a PWM output signal to the IRF540 mosfet when the output temperature value is in line with the reference value and vice versa. The test of this tool was carried out by comparing measurements between the author's prototype tool and the standard measuring tool, namely the digital thermometer. Based on the test results, this device can produce a minimum temperature of 140C at 30-minute intervals without any media. The trial using 330ml bottled water can reach a temperature of 170C within 30 minutes in the cooler box. This tool is also equipped with an automatic monitoring system using a PWM signal in the form of a change in fan speed, which is 255 RPS maximum speed and when getting a PWM signal it changes to 50 RPS. The percentage of errors resulting from the comparison of standard measuring instruments and sensor values had the highest and lowest percentages of 2.37% and 0.84% in cold dispersion conditions without charge. Then the highest and lowest error percentages were 1.69% and 0.72% in the state of containing a load of 1 330ml mineral bottle. This ptototype uses data recording using Micro-SD as a data logger.

Sterilization is the eradication of materials, substances, or tools from various live microorganisms or their resting stages. Bacterial and fungal vegetative cells can be killed at a temperature of 60 °C within 5 to 10 minutes. A data logger is a tool used to monitor the temperature inside an autoclave. Previous research on "Autoclave Data Logger" aimed to assist in recording temperature activities within the autoclave. When the device is turned on, it automatically records the temperature inside the autoclave and stores the temperature data read on an SD card. After the sterilization process is completed, the SD card is retrieved for reading on a personal computer in Excel format or converted into a graph. Therefore, the author developed an IoT-based autoclave calibrator tool with data storage. This IoT-based autoclave calibrator tool with data storage utilizes the ESP32 microcontroller for programming and as a source in the IoT system. The ESP32 is used to control the input from the waterproof DS18b20 sensor, which functions to read or detect the temperature in the autoclave. The data read by the sensor will be displayed on the IoT platform, which is the Blynk IoT application, and after the results are displayed on the IoT platform, they will be stored on an SD card.      

This study aims to determine quality control at PT. JOGJATEX, find out the factors that cause product defects, find out what are the main problems that cause product damage. and provide solutions to reduce the level of product defects. PT JOGJATEX which is engaged in textile knitting. The method used in this study is the Seven Tool Seven tools method is a graphical method used to solve problems in the field of production, especially problems related to quality (Quality). These seven tools or seven basic tools were discovered and introduced for the first time by Kaoru Ishikawa in 1968 who was a figure of quality management innovation in Japan. The conclusion of this study is regarding the production defect report at the Jogjatex company. This product defect is affected by internal and external influences. These factors are basically influenced by several factors including temperature, human resources and machines. The solution taken to overcome the problem in this research is to design a room temperature detector, namely the DS18B20 Temperature Sensor.

Healthcare facilities such as hospitals produce significant amounts of waste from operational and supportive activities. Proper treatment of hospital waste is crucial to prevent negative environmental impacts. Hospital waste and sewage refer to the waste and sewage generated during hospital operations and related activities. Wastewater treatment plants (WWTP) are used to treat liquid waste in hospitals. Currently, wastewater treatment monitoring is conducted manually, posing a threat to the authorities. Wastewater samples are required to be sent to the laboratory that prolongs the duration of results for monitoring wastewater treatment. Inspired by the issue of hospital waste treatment, a monitoring tool for hospital waste treatment is designed employing Arduino, a water pH sensor, and a temperature sensor to diminish the impact of hospital waste. This tool would facilitate the officers in sending samples to the laboratory. The designed tool allows the officers to monitor the hospital wastewater treatment plant's status without the need to visit the plant physically. Water treatment plant monitoring using IoT technology involves the use of a pH sensor, a ds18b20 temperature sensor, and an ultrasonic proximity sensor. This monitoring tool is expected to be used safely to monitor water treatment plants..

Water is very important for all aspects of life on earth, agriculture is one of the fields that really need large amounts of water because of the use of water in the process of plant photosynthesis. Water that has good quality is if the water is not excessively polluted by harmful chemicals or minerals. One indicator that water is polluted is a change in temperature and pH (acidity) of the water. Temperatures that are too hot in the water will interfere with the growth of plants and other microorganisms. While the normal pH of water has a pH that ranges from 6.5 to 7.5. The quality of water and soil is very important in agriculture. The level of acidity (pH) and soil temperature are one of the things that affect plant fertility. Therefore, the quality of water and soil on agricultural land is one of the important things that needs special attention in its management. One solution so that water and soil quality can be monitored and managed efficiently is to utilize a Wireless Sensor Network based on the Internet of Things (IoT). The use of the ESP8266 Module as a WIFI module, is widely used by Internet of Things-based applications because the price is cheap so it reduces a lot of costs and has a fairly good speed of 80 MHz. This study aims to develop the concept of a Wireless Sensor Network by utilizing the ESP8266 module to monitor pH values using a pH Meter Analog Kit sensor and temperature from agricultural land using a DS18B20 Waterproof sensor and can be monitored at any time using a smartphone.

This research was carried out by comparing the DS18B20 sensor and the MLX 90614 sensor to detect the accuracy of detecting human body temperature which is used to detect Covid 19 symptoms. In this experiment, 10 trials were carried out with different human segments detected using the sensor. In the experiment, it was found that the MLX90614 sensor is more suitable to be used for development with an IoT-based system because it does not need to come into contact with the skin of the human body. The MLX90614 sensor will detect the temperature and change it to one Celsius unit then send it to the firebase database which will then be picked up by the android application which is held by the security officer so that the temperature can be known remotely. When the temperature is more than 38.5 Celsius it will turn on the buzzer sound which can be heard from a distance which indicates the temperature is above 38.5 Celsius and on android will also display a danger sign

Aquascape merupakan seuatu hobi yang mulai memiliki banyak peminat. Karena keindahannya banyak masyarakat yang mencoba untuk menekuni hobi ini. Masalah yang sering dialami penghobi baru aquascape adalah minimnya pengetahuan dan waktu untuk merawat aquascape. Dengan memanfaatkan logika fuzzy sugeno, penghobi dapat dimudahkan dalam perawatan dasar aquascape berupa menjaga tingkat ammonia tetap rendah, menjaga suhu air agar tidak melebihi suhu 30℃, menjaga ketinggian air, dan penyinaran menggunakan lampu secara otomatis menyesuaikan intensitas cahaya matahari. Alat ini menggunakan sensor MQ137 untuk membaca gas ammonia, sensor DS18B20 untuk membaca suhu, sensor HC SR-04 untuk membaca ketinggian air, dan sensor LDR atau Light Dependent Resistor untuk membaca intensitas cahaya. Hasil dari penelitian ini yakni sistem mampu memperkirakan output berdasarkan nilai input dari sensor, mampu menjaga tingkat ammonia tetap rendah, menjaga suhu tetap dibatas optimal di sekitar 26 - 28℃, ketinggian air dapat dijaga pada posisi 1 cm lebih rendah dari bibir aquarium dan penyinaran menggunakan lampu dapat menyesuaikan durasi berdasarkan nilai pembacaan sensor LDR