Wireless network technology-based internet of things (IoT) has increased significantly and exciting to study, especially vital sign monitoring (body temperature, heart rate, and blood pressure). Vital sign monitoring is crucial to carry out to strengthen medical diagnoses and the continuity of patient health. Vital sign monitoring conducted by medical personnel to diagnose the patient's health condition is still manual. Medical staff must visit patients in each room, and the equipment used is still cable-based. Vital sign examination like this is certainly not practical because it requires a long time in the process of diagnosis. The proposed vital sign monitoring system design aims to assist medical personnel in diagnosing the patient's illness. Vital sign monitoring system uses HRM-2511E sensor for heart detection, DS18b20 sensor for body temperature detection, and MPX5050DP sensor for blood pressure detection. Vital sign data processing uses a raspberry pi as a data delivery media-based internet of things (IoT). Based on the results of the vital sign data retrieval shows that the tool designed functioning correctly. The accuracy of the proposed device for body temperature is 99.51%, heart rate is 97.90%, and blood pressure is 97.69%.

At this time the development of science leads to the development of technology whose aim is to facilitate all activities and human work. In the medical field even the technology used is increasingly developing more practical, effective and efficient. In the medical world a physical examination or clinical examination is a process carried out by a medical expert to examine a patient's body so that it can find clinical signs of the disease. The use of technology in the medical field today requires a technology that can automatically record the condition of one's blood pressure and body temperature. With the technology that can automatically show the value of clinical examination results are expected to make it easier in the examination. By using NodeMCU which converts the voltage to a digital value and displays it on Android and the MPX5050DP sensor to measure blood pressure and the DS18B20 sensor to measure body temperature, the value sent by the sensor will be processed and displayed on Android. The measurement results are in the form of quantities corresponding to the measured unit such as mmHg (Millimeter of Mercury (Hydrargyrum)) for blood pressure and ˚C for temperature. Results are displayed on the android display. Tests on the device resulted in an error rate from the MPX5050DP sensor of 1.13% for systolic blood pressure, 0.95% for diastolic blood pressure, and at a temperature sensor of 0.5%.

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The PLTB module output monitoring system (wind (wind)) is based on a data logger, which in this study was carried out by designing a tool using an INA219 sensor to measure current and voltage, and using Arduino Uno as a data controller and liaison as well as sending the measurement data. sensor to a Laptop whose readings use the PLXdaq application. Based on the research that has been done, this monitoring system shows that it is an efficient and portable monitoring system and PLTB data can be accessed easily via a laptop and can be read directly using the LCD (liquid crystal display). Where the measurement results are in the form of quantities that are in accordance with the measured units such as A (amperes ) for current and V ( voltage ) for voltage, where the results will be displayed through the PLXdaq application in real time. The results of sending current and voltage data on the PLXdaq application have an error that does not exceed 1%.

The wind is one of the new renewable energy sources that can be used as a source of electrical energy. But the wind in nature has a speed that varies greatly with each time and place. This can be overcome by using the DC-DC Converter tool with a fuzzy method to produce a stable electrical voltage so that it becomes usable electrical energy. This tool uses a series of converters connected to the Arduino microcontroller. The DC-DC converter circuit in this study also uses a voltage sensor as feedback for the Fuzzy method to maintain the stability of the circuit output which varies from 2V-5V, so that it can maintain a voltage of 6.5V which is used as a 6V battery charging. This circuit has an average efficiency of 60% for the open-loop system and 63% for the closed-loop system.