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Stroke is a physical disability disease, which affects the upper extremity motor system. To support post-stroke motor rehabilitation, research on IoT-based elbow exoskeleton therapy devices that help elbow therapy with flexion and extension movements. The therapy device uses DS-SERVORD5160 as the main driver to provide flexible movement. By using the ESP32 microcontroller control system equipped with a Bluetooth connection that is connected via the MIT App Inventor application from a smartphone that can be done at home to increase the effectiveness of post-stroke recovery. The results of this study with low (20°), medium (40 °) and high (60 °) modes by providing a maximum load of 2 Kg. It can be concluded that the device shows stable performance in low (20 °) and medium (40 °) modes, but in testing with high mode (60 °) with a load of 2 Kg there is a decrease in servo performance which is indicated by the instability of the servo movement which shows an angle of 56 °.

This project aims to design and develop a prototype system based on gesture sensors to monitor visitors and smoke sensors to detect the presence of smoke in designated smoking rooms. The system is designed to enhance comfort, safety, and operational efficiency in multipurpose buildings. Utilizing the Arduino Uno microcontroller, the device is equipped with various components, such as a gesture sensor to detect visitor movements entering and exiting the building, enabling visitor monitoring for resource allocation. Meanwhile, the smoke sensor is designed to identify and monitor smoke concentration in the smoking room to prevent the spread of smoke to other areas.The device also includes additional features, such as an automatic exhaust fan and an LCD display for process monitoring. Test results show that the developed prototype has a high accuracy rate in detecting visitor gestures and can reliably and quickly detect the presence of smoke. This system provides an innovative solution to support smarter, safer, and more eco-friendly management of multipurpose buildings. This research is expected to serve as a foundation for further advancements in the application of sensor technology in public facilities.

Stunting disease describes abnormalities in a child's body caused by impaired physical growth. Research has been carried out on Stunting which produces the causal factors and long-term risks for Stunting sufferers. It is hoped that there will be technology that can detect Stunting growth early on in children, so that it can be treated quickly. Therefore, it is necessary to design a Prototype Stunting Detection System using a Microcontroller Based on Ultrasonic Sensors and Load cells which aims to identify Stunting factors for children in the Posyandu working area of ​​Garut Regency. The methodology used is a Prototype Model and uses a black box testing method. As a result, the existence of this Stunting detection system Prototype contributes to Posyandu officers and children so that they can be detected early so that later prevention can be carried out so that it does not grow until the child is old, so that the percentage of Stunting growth can decrease.

The shipping industry faces challenges in reducing environmental impact and increasing operational efficiency. Among them are the expansion tanks on ship engines which play an important role in maintaining the pressure and water quality of the engine cooling system, which is still run manually on some ships. This can result in the risk of engine damage due to overheating or unstable pressure. Manual water filling that requires crew supervision can cause operational instability. This research designed a prototype of an automatic water filling system for expansion tanks, using microcontroller-based automation technology and an Internet of things system to make monitoring easier. This system aims to increase efficiency and reduce the risk of engine damage, thereby supporting the sustainability of ship operations in the future. In the trials that have been carried out, this tool is able to operate the expansion tank filling automatically and efficiently. The distance sensor used has high accuracy with a largest error of 1.6%, and an average error of 0.01%. Integration with the Internet of Things system can run well and reliably with 100% success and latency of 0.5 – 1 second. The system's overall success rate is 80%. So the system can be used in real working conditions

Sleep disorders such as insomnia are health problems that have a serious impact on quality of life. This research aims to design and build a brain wave stimulator based on Audio Visual Stimulation (AVS) as a non-invasive solution to help improve sleep quality. It utilizes a synchronized combination of light and sound, controlled by an Arduino NANO microcontroller, and supported by a DFPlayer Mini module, speakers, and blue LEDs as a stimulation medium. The research methods used are applied research with observation stages, literature studies, system design, tool implementation, and function testing. Functional tests were performed five times in a span of 15 minutes after the device was activated. The results of the voltage measurement on each component also show that the performance of the tool is within normal limits according to the datasheet. Thus, this tool successfully functions as designed and has the potential to be a viable solution to improve sleep quality.

The increasing unpredictability of climate change demands a system capable of automatically detecting rainfall and providing early warnings. This study aims to design and develop a rain detection system based on a water sensor and LED using an Arduino Uno microcontroller. The system operates by detecting water presence on the rain sensor and providing a visual indication through an LED. The research methodology follows a Research and Development (R&D) approach, including literature review, hardware and software design, implementation, and system testing. The test results indicate that the system can accurately detect rainfall and respond to weather changes in real-time. This system has the potential to be applied in various sectors, such as agriculture, transportation, and industry, to mitigate risks caused by sudden rain. Further development can integrate Internet of Things (IoT) technology for remote weather monitoring.

Improving efficiency and quality in ironing and folding clothes is a primary concern in modern households. This research aims to develop a prototype of an automatic ironing and folding device that enhances productivity while reducing processing time compared to manual methods. Testing was conducted on three types of fabric materials: polyester, cotton, and linen, by comparing time and folding quality between the automatic and manual methods. The results showed that the automatic prototype completed the process in an average of 5 minutes for all fabric types, compared to 8 minutes with the manual method. In terms of folding quality, the automatic prototype demonstrated more consistent results with a high level of neatness across all fabric types. The conclusion of this study is that using the automatic ironing and folding prototype provides significant time efficiency and improves quality compared to the manual method. These findings contribute to the development of more effective and efficient household technologies.  

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.

The human body cannot work properly without water. Therefore, it is essential to conduct testing and monitoring of drinking water quality to ensure its safety and suitability for consumption. This has prompted researchers to develop more efficient systems compared to traditional methods. This study employs a systematic literature review approach by analysing various published articles to identify and evaluate the application of different types of sensors capable of detecting physical and chemical parameters for assessing drinking water quality. The findings indicate that the integration of sensors, microcontrollers, and Internet of Things (IoT) technology can provide accurate data that is accessible in real-time and remote locations. Furthermore, to enhance the reliability of the system, it is necessary to further develop data processing algorithms by applying artificial intelligence (AI) and/or machine learning technique to create smart systems with improved predictive capabilities. The implementation of these technologies is expected to support the Indonesian government’s Sustainable Development Goals (SDGs) by providing safe and affordable access to drinking water for all its citizens.

The rapid development of digital technology has introduced new challenges in IT project management. Microcontrollers, typically used in hardware systems, offer innovative solutions to address these challenges. This article aims to explore the role of microcontrollers in IT project management information systems, focusing on task automation, real-time data collection, and IoT device management. The research examines the application of microcontrollers in optimizing efficiency and accuracy in managing digital projects. Key findings indicate that microcontrollers can significantly enhance monitoring, control, and analysis of projects, providing better insights for project managers in making strategic decisions. In conclusion, microcontrollers offer effective modern solutions to current digital project challenges.

Microcontroller-based information systems play a crucial role in enhancing the efficiency and effectiveness of various automation and monitoring applications. However, many manual processes across different fields require time and are prone to errors. This study aims to develop a microcontroller-based information system to automate real-time data collection and monitoring in various applications, such as industry, environment, and smart homes. The method used involved the development of a prototype system designed to integrate sensors and microcontrollers in data processing and automated decision-making. The results showed that this system significantly improved the efficiency, accuracy, and speed of data processing while minimizing human intervention. In conclusion, microcontroller-based information systems offer innovative solutions that can be widely applied across various fields to enhance performance and service quality.

Microcontrollers play a vital role in managing patient data systems within hospital environments, including at Kisaran General Hospital. A microcontroller-based data management system facilitates the automation of patient data recording and processing in real time, enhancing both accuracy and efficiency. This study aims to analyze the performance of microcontrollers in a patient data system by evaluating parameters such as processing speed, data accuracy, and system stability. The implementation involves an Arduino Uno microcontroller integrated with sensors and data processing software. Experimental results demonstrate the system's ability to process patient data quickly and accurately, contributing to the operational efficiency of the hospital. These findings highlight the potential of microcontroller technology as a modern solution for patient data management in healthcare settings.

The Arduino microcontroller plays a significant role in automation systems, including temperature control in industrial settings. Its implementation addresses challenges related to accuracy and efficiency in control systems. By applying a temperature control system based on the Arduino microcontroller, the control process becomes more effective and efficient, taking into account parameters such as target temperature, response time, and system stability. This study utilizes the integration of a temperature sensor with an Arduino Uno-based controller to monitor and regulate temperature in real-time. Data from experiments demonstrate high system accuracy in maintaining the target temperature range. These findings support the application of Arduino microcontrollers in improving efficiency and quality in industrial temperature control.  

Financial information systems play a crucial role in managing and processing company financial data. However, manual data collection and processing often require time and are prone to errors. This study aims to optimize financial information systems by utilizing microcontrollers in the automation of data collection and processing. The method used involved the development of a microcontroller-based prototype system to automate real-time financial data monitoring and reporting. The results showed that the use of microcontrollers significantly improved the efficiency and accuracy of financial data processing, while reducing the time needed for reporting. In conclusion, a microcontroller-based system can be an effective solution to enhance the quality and speed of financial data processing in companies.

This research focuses on the design and implementation of an automatic parking barrier system using a microcontroller. The objective is to create an efficient and reliable system that automatically controls the parking barrier in response to vehicle detection. The system utilizes an infrared sensor for vehicle detection, which is processed by a microcontroller to control a servo motor for opening and closing the parking barrier. The research method includes simulation using Proteus software followed by physical implementation. Results show that the system operates efficiently with a quick response time of 1-2 seconds for barrier movement. The conclusion is that the system is effective in automating parking barrier control, reducing human error, and improving parking management. Further improvements can be made by enhancing sensor sensitivity and integrating additional technologies.  

Coffee is an agricultural product highly favored by the majority of the Indonesian population. Coffee comes in various types, each with a distinct aroma. Currently, differentiating coffee types relies on conventional methods, using the human nose, which is shubjective and dependent on individual conditions. This approach is less effective. To address this, researcher have developed a machine learning based system using Arduino Mega 2560 as the microcontroller, gas sensor MQ4, MQ7, MQ135, as the aroma detection tools, and the Linear Discriminant Analysis (LDA) algorithm as the classification method. The results of this system can classify 5 types of coffee with an accuracy rate of 90%.

This paper presents an IoT-enabled dual-axis solar tracking system that integrates  a Kalman filter and a Proportional-Integral-Derivative (PID) controller to enhance tracking accuracy, energy efficiency, and operational stability. Addressing the ongoing challenge of maxi- mizing photovoltaic (PV) panel output, the proposed system leverages an ESP32 microcontroller and the Blynk platform to provide real-time monitoring, remote parameter adjustments, and flexible connectivity. Light Dependent Resistor (LDR) sensors measure sunlight intensity from multiple directions, while MG90S servo motors dynamically adjust the panel’s azimuth and elevation. The Kalman filter refines noisy sensor data to yield precise sun position estimates, enabling the PID controller to respond quickly and accurately to deviations in panel orientation. Through extensive testing conducted over several days, including both clear and partially cloudy conditions, the system achieved an average Root Mean Square Error (RMSE) as low as 1.2° under clear skies and maintained RMSE below 2.0° even under partial shading. Compared to a fixed-panel baseline, daily energy harvesting improved by approximately 43%. These results confirm that advanced estimation and control algorithms, when combined with IoT functionali- ties, significantly outperform simpler tracking methods and static installations. Furthermore, the low-cost, compact design and user-friendly interface facilitate practical deployment in a range of scenarios, including small-scale and off-grid installations. By ensuring continuous alignment of the PV panel with the sun, the system not only increases overall energy capture but also reduces maintenance requirements through remote oversight. This research thus offers a robust, scalable approach to improving solar energy utilization in diverse and evolving environmental conditions.

This study aims to develop a color detection application based on microcontrollers as an intelligent solution for visual identification. The application is designed to accurately detect and identify color spectrums using a color sensor integrated with a microcontroller. A project management approach in informatics engineering was applied to ensure the effective design and implementation of the system. A qualitative descriptive method was employed in this research, including data collection through device testing and interviews with potential users. The results demonstrate that the application can recognize colors with high accuracy, making it applicable across various fields such as industry, education, and assistive technology. Supporting factors for the application's success include hardware and software compatibility, while the main challenges involve the impact of light intensity on sensor performance. Further development is recommended to enhance the application’s performance in more diverse operational environments.

This research aims to design and build a system for stirring and monitoring temperature and humidity for ESP32-based compost fertilizer. This system uses an ESP32 microcontroller to control compost mixing and monitor temperature and humidity conditions in real- time. Data obtained from sensors will be sent to the server for monitoring via Blynk. The implementation of this system is expected to increase the efficiency of the composting process and produce high quality compost through optimal monitoring and mixing.

This paper presents the design and implementation of an automatic Virgin Coconut Oil (VCO) making device using an Arduino Uno microcontroller. Virgin Coconut Oil has gained popularity due to its health benefits and versatile uses in various industries. The traditional process of making VCO involves manual effort and precise timing, which can be tedious and inconsistent. The proposed automated system aims to streamline the VCO production process by integrating sensors, actuators, and a microcontroller to achieve precise control and monitoring of the process variables. The Arduino Uno microcontroller serves as the central unit for data acquisition, processing, and control, facilitating automation through programmed logic. Key components of the automated VCO maker include temperature sensors for monitoring heating stages, a motor for stirring, and relays for controlling heating elements. The system utilizes feedback loops to maintain optimal conditions during each phase of VCO production, ensuring reproducibility and quality. The design also emphasizes user-friendly operation, with an interface that provides real-time feedback on process parameters and allows manual intervention if necessary. Safety features are incorporated to prevent overheating and ensure operational reliability. Overall, the developed automatic VCO maker offers a practical solution to enhance the efficiency and consistency of VCO production, catering to both small-scale producers and commercial enterprises in the food and cosmetic industries