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The rapid development of technology in the era of the Industrial Revolution 4.0 has driven the education sector to continuously adapt to the evolving demands of digital-based industries. One of the key technological innovations supporting this transformation is the Internet of Things (IoT), which enables data acquisition, real-time monitoring, and remote control of systems through internet networks. In response to these developments, a community service program was conducted to enhance the understanding and technical skills of students at SMK Negeri 1 Sindang through the provision and utilization of an IoT Trainer Kit Simulator as a practical learning medium. This activity aimed to bridge the gap between theoretical knowledge and industry-relevant technological applications by introducing students to hands-on IoT system implementation. The program included demonstrations and guided practice on the use of sensors, microcontrollers, and web-based monitoring platforms to simulate real-world industrial scenarios. The results indicate that students showed high enthusiasm and active participation throughout the activity. Moreover, participants were able to grasp the fundamental concepts of IoT systems, understand component integration, and recognize the relevance of IoT applications in supporting automation and digital transformation. Overall, this community service activity contributed positively to strengthening students’ digital competencies and preparedness for the demands of the contemporary industrial and technological landscape.

The development of automation and robotics technology has driven innovation in various industrial fields, particularly in automatic sorting systems. Manual sorting processes often lead to inefficiencies and human errors, creating the need for an automatic, fast, and accurate system. This research employs a qualitative method which includes experimentation, testing, and system documentation. The system is designed as a robotic arm for sorting objects based on color, utilizing a TCS3200 color sensor and an ESP32 microcontroller. An ultrasonic sensor detects the presence of objects, while the sorting results are displayed through a real-time web monitoring system. The test results show that the prototype successfully sorts four primary colors (red, green, blue, and yellow) with a high level of accuracy. This research is expected to serve as a reference for the development of automation systems and robotics learning tools in both educational and industrial applications. In addition, this research also contributes to the development of technology that can increase efficiency and accuracy in industrial production processes and provide more environmentally friendly solutions by reducing the need for manual labor.

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.

The integration of Digital Signal Processing (DSP) algorithms in low power microcontroller based embedded systems has emerged as a promising solution to optimize energy efficiency without compromising signal accuracy and performance. This study focuses on the design and optimization of DSP algorithms specifically for microcontrollers, aimed at achieving real-time, reliable monitoring for applications such as healthcare, environmental sensing, and IoT devices. The research highlights the system's ability to handle complex signal processing tasks while maintaining low power consumption, ensuring long-term, continuous operation in remote or battery-powered environments. The system employs various techniques, including advanced power management strategies such as dynamic voltage scaling (DVS) and adaptive voltage scaling (AVS), along with lightweight AI algorithms and model pruning, to minimize energy use. The results show significant reductions in power consumption compared to traditional systems, particularly during continuous monitoring tasks. Despite this, the optimized DSP algorithms maintain or even enhance signal accuracy, ensuring that critical monitoring data remains reliable. Furthermore, the system demonstrates robust performance and reliability over extended periods, making it suitable for long-term deployment in critical applications such as wearable medical devices and industrial sensors. This research provides a foundation for the development of future low power embedded systems, emphasizing the importance of DSP-aware optimization in achieving energy-efficient and high-performance monitoring. Future improvements may include advanced AI-driven power optimization techniques, enhanced scalability, and cross-domain interoperability, ensuring that these systems can be effectively deployed across diverse applications, from healthcare to environmental monitoring.

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

This study discusses the design and development of an automatic safety system for a wood cutting machine using Arduino Uno, a PIR (Passive Infrared) sensor, and a servo motor as the main components. The system is designed to automatically stop the movement of the wood cutting machine when human motion is detected around the cutting area, thereby minimizing the risk of work-related accidents. The research method includes hardware design, microcontroller programming, and system response testing using two types of test objects: the human body and a wooden block. The results show that the system operates according to the programmed logic. When the PIR sensor detects human motion, the servo motor stops and the red LED lights up as a danger indicator. In contrast, when no human motion is detected, the servo motor continues to move normally and the green LED remains on as a safe indicator. The system’s average response time is 0.6 seconds, indicating a fast and accurate performance. Therefore, the designed system is considered effective and can serve as a prototype of a simple safety tool to enhance operator safety in wood cutting machines.

Indonesian Sign Language (BISINDO) serves as a primary communication medium for the deaf community; however, limited public understanding often creates barriers during daily interactions. This study aims to develop a real-time BISINDO word-level translation system using hand landmark extraction and temporal modeling with Long Short-Term Memory (LSTM). The system employs MediaPipe Hands to detect 21 hand landmarks per frame, which are then processed as sequential motion patterns to classify five BISINDO words: saya, terima kasih, maaf, nama, and kamu. A total of 250 gesture samples were recorded under controlled lighting conditions as the primary dataset. The processed sequences were used to train the LSTM model, which was subsequently integrated with an ESP32 microcontroller and a DFPlayer Mini module to produce direct audio output. Experimental results show that the model achieved an average accuracy of 86%, with precision and recall values ranging from 0.81 to 0.94. The confusion matrix analysis indicates that most gestures were correctly classified, although some errors occurred in gestures with similar initial motion trajectories. Integration testing demonstrated an average system latency of 3.8 seconds and an audio output success rate of 85%. These findings indicate that the proposed system is capable of translating BISINDO word-level gestures accurately, responsively, and consistently in real-time conditions. This study provides a strong foundation for the broader development of sign language translation systems, with potential enhancements in vocabulary expansion, multi-user datasets, and hardware optimization for deployment in real-world environments.

The manual employee attendance process at the Perjuk Village government level often results in inaccurate data, delayed recapitulation, and difficulties in real-time attendance monitoring. This study aims to develop an Internet of Things (IoT) and Radio Frequency Identification (RFID)-based village employee attendance system to simplify the administrative process and improve the efficiency of attendance recording. The development method used is the Research and Development (R&D) model with stages including needs analysis, system design, validation, field trials, and product revisions. The system was built using an ESP32 microcontroller, an RC522 RFID module, and a Wi-Fi connection to transmit attendance data to a web-based server. Testing was conducted using the black box method to ensure all system features run according to design. The results of the black box test show that all features run according to design. The system records attendance automatically with 100% accuracy, saves data to the server database, and displays reports in the form of tables, graphs, and statistical cards. The study concludes that this IoT and RFID-based attendance system is able to improve the accuracy, speed, and efficiency of recording compared to manual methods, and is in accordance with operational needs at the Perjuk Village Office.

The main problem with the water heating system on offshore platforms is the absence of water level monitoring and automatic overflow detection. This has the potential to cause hot water spills that endanger workplace safety and operational efficiency. This research designs and implements a water level monitoring system based on the Arduino Uno microcontroller with HC-SR04 ultrasonic sensors. The system is equipped with LED indicators, a buzzer alarm, and a 16x2 LCD to display water level status in real-time. Water levels are classified into three zones (low, medium, high), and overflow is detected if the water is within 3 cm of the sensor. Testing was conducted on a 5-liter simulation tank representing actual 500-liter tank conditions. Test results showed a reading accuracy of 96% and a quick system response to overflow conditions (<1 second). This system is economical, easy to develop, and highly applicable for offshore environments. In addition, this system can be integrated with IoT technology for remote monitoring.

The braking system is a crucial component in a vehicle, where its performance is highly influenced by the wheel's rotational speed and the geometry of the brake pad. This study aims to analyze the impact of wheel rotational speed and variations in pad geometry on the temperature of the brake pad. The braking process generates heat due to friction, which, if not properly managed, can reduce braking performance and accelerate brake pad wear. The experiment was conducted at four levels of wheel rotational speed: 1000 RPM, 1500 RPM, 2000 RPM, and 2500 RPM. The testing system was designed using a braking system simulator equipped with a speed sensor (LM393) and a temperature sensor (K-type thermocouple), which were connected to an Arduino microcontroller and displayed in real-time through a Graphical User Interface (GUI) in MATLAB. The test results indicated that both the geometric shape of the brake pads and the wheel rotation speed significantly affected the resulting temperature. Standard brake pads produced the highest temperature at a speed of 2500 RPM, reaching 63.33°C. In contrast, brake pads with holes offered the best performance by maintaining a lower temperature of only 43.00°C. Furthermore, an increase in wheel rotation speed led to a noticeable rise in temperature; for standard pads, the temperature increased from 36.67°C at 1000 RPM to 63.33°C at 2500 RPM. This demonstrates that RPM is a major factor in heat generation due to friction. The MATLAB GUI effectively visualized the relationship between RPM and temperature, facilitating the analysis and evaluation of the data.

Waste management remains a major challenge, particularly due to the lack of public awareness and habits in sorting waste from its source. Innovative technology-based solutions are needed to support more effective waste management systems. This study aims to design and develop an Internet of Things (IoT)-based smart trash bin capable of automatically sorting metal and non-metal waste. The system utilizes an ESP32 microcontroller as the main controller, an LJ12A3-4-Z/BY sensor to detect metal materials, an E18 sensor to detect non-metal materials, and an ultrasonic sensor to monitor bin capacity. The waste separation mechanism is operated by a servo motor controlled by the system, while the Blynk application is integrated for real-time monitoring and full-capacity notifications sent directly to the user’s smartphone. The research stages included hardware design, microcontroller programming, IoT platform integration, and functionality testing to ensure system performance and reliability. The results showed that the smart trash bin operated as expected, successfully identifying and separating metal and non-metal waste automatically, while also sending real-time notifications to the user when the bin approached full capacity. The implementation of this technology has the potential to modernize waste management processes, improve the efficiency of waste sorting, and reduce dependency on manual labor. Furthermore, this research opens opportunities for future development by integrating additional sensors and cloud-based data management systems to support smart city initiatives and sustainable waste management practices.

Manual post-harvest paddy stirring requires significant time and labor and often results in uneven mixing, which can affect grain quality. To address this issue, this study designed and implemented a prototype of an Internet of Things (IoT)-based paddy stirring robot to simplify the process and improve efficiency. The system utilizes an ESP32 microcontroller as the main controller, DC motors as the stirring mechanism, and an IoT module for wireless connectivity to a mobile application. The research stages included hardware design, control system programming, IoT platform integration, and performance testing. Testing was conducted to evaluate response time, mixing uniformity, and power consumption. The results showed that the system could be operated remotely via a local Wi-Fi network with an average delay of less than 1 second, enabling real-time control. The prototype successfully stirred 0.3 kg of paddy with a mixing uniformity rate of 92% and an average power consumption of 12 watts. The application of IoT in the paddy stirring mechanism significantly improved time efficiency, reduced manual labor requirements, and maintained grain quality compared to traditional methods. These findings indicate the potential for further development into a large-scale automated paddy processing system with integrated humidity and temperature sensors for real-time quality monitoring, supporting the modernization of post-harvest processing through digital technology.

The development of embedded sistem technology is now widely used to support automatic environmental data recording processes, such as temperature, humidity, and air pressure. However, most existing weather data loggers still operate independently and are not directly connected to a computer. As a result, data collection and processing must be done manually, which is less efficient and prone to data loss. The main problem in this research is the lack of integration between microcontroller-based data loggers and simple computer operating sistems such as the Disk Operating Sistem (DOS), making it difficult to automatically store and access recorded data. This study aims to develop an embedded weather data logger sistem based on the AVR microcontroller integrated with DOS. The development process uses the waterfall model, consisting of sistem planning, requirement analysis, sistem design, coding, testing, and implementation. The designed sistem records weather parameters in real time and stores them in a file format that can be directly read by DOS without requiring additional conversion processes. The test results show that the sistem runs stably, records data accurately, and can be easily accessed through a computer. Integration with DOS allows data storage and retrieval processes to be faster and more efficient. Therefore, this sistem provides a practical solution for automatic weather monitoring that is reliable, time-saving, and easy to use in various environmental conditions.

Android continues to innovate, and biometric systems particularly fingerprint sensors must operate with high efficiency. However, the main challenge lies in the communication between hardware and software, which often causes high latency, excessive power consumption, and protocol incompatibility between components. As a result, authentication speed decreases and system stability is compromised, especially on mid- to low-range devices. This study explores various implementations of Android-based fingerprint systems, focusing on how sensor modules interact with the microcontroller or Trusted Execution Environment (TEE) and the operating system through a hardware-software co-design approach to evaluate integration efficiency across all layers. The analysis reveals that conventional protocols such as Bluetooth or serial connections still cause delays, while improvements in drivers and the Hardware Abstraction Layer (HAL) can significantly reduce latency. As a solution, the researchers propose a co-design optimization approach that utilizes data flow normalization within the HAL and adopts lightweight communication protocols to accelerate the verification process. Based on the test results, this approach successfully improves efficiency—authentication time is reduced by up to 35% and power consumption decreases by approximately 15%. Therefore, the efficiency of communication between hardware and software becomes a key factor in enhancing the performance and reliability of fingerprint systems on Android devices.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

The braking system was a crucial component in ensuring the safety of motor vehicles on the road. Brake failures, such as brake fade or total malfunction, could result in fatal accidents. Therefore, an accurate and realistic testing method was necessary to measure the effectiveness of a vehicle’s braking system. This study aimed to develop a deceleration measuring device based on GPS, which could be used in road test methods. The device was designed using an ESP32 microcontroller combined with a BN-220 GPS module, RTC real-time clock sensor, 16x2 LCD, thermal printer, and microSD storage media. Testing was conducted on a Mitsubishi L300 vehicle at the Depok Beach runway in Yogyakarta, with initial speed variations ranging from 10 to 80 km/h. Calibration results showed that the device had an accuracy of 99.64% with an average error of 0.36%. Meanwhile, the test results recorded deceleration values ranging from 0.74 to 3.26 m/s², depending on the initial speed and braking conditions. Based on these findings, the developed device proved to be accurate and feasible as an alternative method for field testing of braking systems.

Modern industries require automation to enhance operational efficiency and productivity. This study designs and implements an automatic sorting system based on the Internet of Things (IoT) using a mini conveyor, ESP32 microcontroller, TCS3200 color sensor, servo motor, and the Blynk application. The system is designed to accurately detect object colors, sort objects based on color, and enable remote monitoring and control via mobile devices. Testing results indicate that the system can detect and sort objects with a high level of accuracy, although some errors occur due to changes in lighting conditions. The conveyor speed is consistently recorded at 0.335 m/s, while the system's response time, including color detection, servo movement, and application updates, operates within an optimal range. The Blynk application enhances the flexibility of real-time system control. This study demonstrates that IoT-based sorting systems can serve as an efficient solution to support industrial automation. Further development is recommended to improve color detection accuracy and expand the system's application in more complex industrial scenarios.

The IoT-based CO and COHb gas detector is a device used to detect the presence of carbon monoxide (CO) gas and the level of carboxyhemoglobin (COHb), supported by Internet of Things (IoT) technology for remote monitoring and real-time reporting. This device will be used in hospital rooms, serving as an important solution in efforts to ensure the safety of patients, medical staff, and hospital visitors. With the presence of the CO and COHb gas detector, hospital staff will find it easier to detect the presence of CO gas in the rooms within the hospital. The operation of this device is quite simple: just place the device in the room in the "on" condition, and it will automatically detect the CO and COHb gas present in that room. The measurement results of CO and COHb gas will be directly sent to Google Sheets for storage of the measurement results. The creation of this device requires several components, such as the ESP32 as the microcontroller, DHT11 as the temperature detection sensor, MQ7 as the CO gas detection sensor, and the application of IoT using a Google Sheets web app to monitor results remotely and store measurement results. According to the analysis of the device created by the researchers, the performance or functionality test results of the CO and COHb gas detector can be used smoothly. The author conducted functional tests or performance tests of the device by measuring data in a free room, roadside environment, motorcycle exhaust smoke, active smokers, and passive smokers.

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.