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Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.

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.

A wall follower robot is a type of autonomous robot that is designed to move by following a wall at a certain distance. This research aims to design and build a Wall follower robot equipped with a Fuzzy-PID control system to improve navigation performance. The robot uses five HC-SR04 ultrasonic sensors to detect the distance to the wall and the surrounding obstacles. The data from the sensor is then processed by a Fuzzy-PID algorithm that combines the advantages of conventional PID control with fuzzy logic, resulting in a more adaptive response to environmental conditions. The test results showed that the robot with Fuzzy-PID control was able to maintain the stability of the distance to the wall more consistently compared to the pure PID control. In addition, the system exhibits better adaptability to complex environmental conditions, such as sharp turns, uneven wall surfaces, and the presence of resistance variations. The application of Fuzzy-PID control has been shown to improve the stability, response speed, and accuracy of the robot's navigation. These findings are expected to contribute to the development of robotic navigation systems for a wide range of practical applications, including automated cleaning robots, environmental exploration, and industrial systems that require reliable autonomous mobility.

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.

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.

Unmonitored traffic conditions often hinder decision-making processes in traffic management, particularly on secondary roads. Jalan Raden Inten II in East Jakarta is one of the connecting routes with heavy traffic activity at certain times, yet no integrated data-based monitoring system is currently available. This study proposes an Internet of Things (IoT)-based traffic condition classification system to identify Clear, Normal, or Congested states based on vehicle counts and speed categorization. The system is designed using an ESP32 microcontroller, an HB100 sensor to detect vehicle speed, and two AJ-SR04M ultrasonic sensors to detect vehicle presence. Data on vehicle counts and the percentage of slow-moving vehicles are periodically transmitted to the ThingSpeak platform and processed using the Threshold-Based Classification method. The classification results are visualized on a dashboard-based website equipped with charts, traffic condition status, and notifications when consecutive congestion is detected. Testing was conducted using simulation data over a specific period. Qualitative validation was carried out by comparing the classification results with traffic indicators from Google Maps. The results show that the system can classify traffic conditions with a good degree of agreement with external references, although discrepancies occurred at certain times due to the limitations of simulated data. This research demonstrates that a simple IoT approach can provide an affordable and effective solution for monitoring and classifying traffic conditions, with potential for real-world implementation in future studies.

Floods are the most frequent natural disasters and cause material and non-material losses. One of the problems faced is the lack of early warning when floods occur. This problem can be overcome with a flood early warning system. This paper discusses the solution to this problem, namely by designing and implementing a real-time flood early warning system using IoT-based Internet of Things (IoT) technology ESP32 MQTT and APK Kodular. The objective of this research, compared to previous studies, shows a gap in the methods used. While previous studies used an IoT-based flood warning system that sends data via SMS or an HTTP server, this study applies real-time monitoring with the MQTT protocol, which allows sending water level data with low latency to the Kodular application for faster and more responsive warnings. The method used is to connect hardware with IoT where ESP32 is a client that sends data to MQTT and will display it in the Kodular APK. This flood early warning system consists of: ultrasonic sensors, ESP32, MQTT cloud, OLED, buzzer, LED, and APK on the phone to receive notifications through a mobile application created using Kodular. This IoT-based system is installed in the Kudu Regency river and can monitor water levels in real-time. Based on a predetermined threshold, the system can activate the LED indicator or buzzer and send an early warning message to the user via the APK on the phone. Test results show that this system functions effectively in providing flood warnings with an accuracy of 1-2 cm and in a timely manner, making it suitable for community-based flood monitoring solutions

This research was conducted from June to July 2025 in Binjai City, with the primary focus being analyzing the readiness of the Binjai City Regional Disaster Management Agency (BPBD) to implement a flood early warning system utilizing artificial intelligence (AI). The data collection process was conducted through a literature review, which involved reviewing various theories and previous research results regarding the application of AI and Internet of Things (IoT) technology in the context of disaster mitigation. Based on the results of the study, it was found that the use of technologies such as ultrasonic sensors, microcontrollers, fuzzy logic, and automatic notification systems can provide real-time warnings with a high level of accuracy and a fast response. This system enables early detection of rising river levels through automatic measurements, intelligent data processing, and sending notifications to authorities and affected communities within seconds. By integrating historical data and machine learning-based predictions, this system is also able to depict potential flooding before it occurs, providing a longer response time for evacuation. However, the readiness of the Binjai City BPBD still faces various challenges, such as limited digital infrastructure, the need for human resource training in the technology field, and inadequate budget allocation. Therefore, cross-sector collaboration and ongoing policy support are needed for optimal implementation of this system. The use of AI and IoT in early warning systems is not only technically relevant but also urgent in the face of increasing climate change and flood risks. A strategy involving cross-sector collaboration between government, academia, and the private sector is needed to develop an adaptive and sustainable early warning system.

Internet of Things (IoT)-based digital transformation has become a major catalyst in improving the efficiency of operational systems in various sectors, including the modern retail industry. One of the common logistics problems found in supermarket environments is the accumulation of unorganized shopping trolleys, which can hinder service flow and increase staff workload. This study presents a design of an IoT-based autonomous smart trolley system and automatic navigation to address these problems in a structured manner. The system design utilizes the integration of ESP32 and Arduino UNO microcontrollers, ultrasonic sensors for distance detection, line sensors for automatic path navigation, and Raspberry Pi modules for visual image processing in location tracking. The system is designed to be able to independently reposition the trolley to a predetermined parking station. Conceptual analysis shows that this system has significant potential in reducing operational costs, increasing labor efficiency, and strengthening customer service automation. Initial evaluation of technical and economic feasibility aspects strengthens the opportunity for widespread system implementation in the future. This design is the first step in developing a smart retail solution based on adaptive technology that is in line with the principles of Society 5.0. Furthermore, the development of this smart trolley system also considers user safety and comfort through additional features such as anti-collision sensors, an early warning system in the event of technical problems, and a manual control option as an alternative in emergency situations. The integration of Internet of Things-based technology also enables real-time monitoring and management systems through a web-based dashboard or mobile application, which can be accessed by supermarket management for operational analysis. Thus, this system not only addresses internal logistics needs but also contributes to improving the overall customer experience.

The Karanggeneng River in Rembang Regency, Central Java, serves as the main water source for the surrounding community but is vulnerable to seawater contamination during the dry season due to decreasing river elevation. To address this issue, this study aims to design and implement a river water elevation monitoring device based on the Internet of Things (IoT) powered by a hybrid Solar Power Plant (PLTS). The device utilizes the MB7360 ultrasonic sensor connected to an ESP32 microcontroller to measure water elevation in real-time and display the data through an LCD and the Blynk application on a smartphone. The methodology includes literature review, device design, system implementation, and field performance testing. Test results show that the sensor can measure water height accurately within a range of 30 cm to 5 meters, and the PLTS system is capable of supplying the required 0.56 Watts of power. The study compared two alternative solutions and selected the ESP32-based system as the best option due to its efficiency, cost-effectiveness, and easy-to-source components. The conclusion of this research indicates that the developed device can provide accurate and continuous information, support monitoring of river conditions to prevent the risk of seawater intrusion, flooding, or drought, and has the potential to be applied as a mobile system in various other river locations across Indonesia.

Methane gas detection is crucial in the oil and gas sector to enhance safety and operational efficiency. This study examines the impact of three types of gas detectors—catalytic, infrared, and ultrasonic sensors—on accuracy and response time. The research was conducted at PT PHM's onshore and offshore sites to evaluate sensor performance in operational environments. A quantitative approach with direct field observation was used. Data were collected by measuring methane gas concentrations indicated by detectors, which were then compared to standard gas concentrations. Response times were recorded when the detectors were exposed to methane concentrations of 2.5% LEL until the alarm triggered at 40% of full scale. Data analysis was performed using descriptive statistics, homogeneity test, normality test, ANOVA, and post hoc tests. The results show that the infrared detector had a response time of 2.87 seconds with an accuracy of 0.218%. The catalytic detector had a response time of 8.91 seconds and accuracy of 0.489% and the ultrasonic detector had a response time of 6.15 seconds and accuracy of 0.842%. Overall, the infrared detector demonstrated the best performance in response time and is recommended for use at PT PHM.

Water is an essential resource for every household. Typically, household water distribution systems rely on PVC pipes and faucets. Despite this, water leakage remains a frequent issue, occurring in both pipes and taps. This study aims to design an Arduino-based automatic faucet control system capable of detecting leaks in water pipes, with the goal of conserving water and improving usage efficiency. The system employs a pressure sensor to monitor water pressure within the pipe, an ultrasonic sensor to detect user presence at the tap, and a solenoid valve to automatically shut off the water supply in the event of a leak. Testing and design outcomes indicate that the system functions effectively. The solenoid valve successfully closes the water flow automatically when a leak is detected. However, the current system lacks a notification feature to alert users when a leak occurs. Future developments should consider integrating a notification mechanism to inform users promptly about any detected leaks.

This applied scientific work is entitled "Design of Automatic Smart Berthing System Based on Arduino". Ships are a comfortable alternative transportation. Currently, ship development is needed so that they can operate properly. During the docking process, ship accidents often occur in ports both nationally and internationally. Therefore, a better development or safety is needed that can be given to ships during the docking process. This tool uses the Arduino Nano microcontroller as the main control and an ultrasonic sensor as a distance counter to prevent accidents. This applied scientific work aims to realize and facilitate work on the ship by abandoning manual methods. Berthing is the location of the ship's mooring or security, the area around the ship where the anchor is thrown, the ship's residence, employing the ship's crew and positioning the ship in the desired place. This scientific paper uses experimental research as its research method. The use of experimental research methods in educational research will be faced with problems concerning research subjects. Experimental research is also research that is carried out intentionally by researchers by providing certain treatments to research subjects in order to create a tool or design that is expected by the researcher.

Efficient and accurate fuel management systems are becoming increasingly important as energy needs and operational complexity increase in various industrial sectors. This study aims to design and implement a fuel flow monitoring and control system using a variable control valve. This system allows real-time monitoring of the level and flow of fuel in the service tank on the ship, as well as automated control. In its implementation, ultrasonic sensors, control valves are combined with LM2596 connected to Arduino nano for data collection, analysis and visualization. The test results show that this system is able to provide accurate data on the flow and level of fuel in the service tank on the ship by displaying the measurement results on the LCD and providing warnings via a buzzer. The LCD display shows the reading of the fuel level and valve opening in the tank. At a fuel level of 0 - 25% the valve will open 100% and requires an average filling time of 25 seconds, At a fuel level of 25% - 50% the valve will open 75% and requires an average filling time of 27 seconds, At a fuel level of 50 - 75% the valve will open 50% and requires an average filling time of 30 seconds, At a fuel level of 75 - 99% the valve will open 25% and requires an average filling time of 32 seconds.

Overhead cranes are an important device in the manufacturing and construction industry that functions to move heavy loads efficiently and safely. However, human error often occurs which can cause work accidents, equipment damage, and decreased productivity. Therefore, this research aims to design and build an Arduino-based automatic overhead crane system that can increase work efficiency and safety. This system is designed using an Arduino microcontroller as a control center, equipped with an ultrasonic sensor to detect the position and distance of the load, as well as a servo motor to regulate crane movement automatically. The system also features a wireless communication module to monitor and control the crane remotely. The research method used is Research and Development (R&D), which includes the stages of needs analysis, system design, hardware and software implementation, and performance testing. Test results show that this automatic overhead crane is capable of moving loads with high accuracy and a speed that can be adjusted according to needs. The system also succeeded in reducing manual intervention, thereby increasing work safety and reducing the risk of accidents by up to 30% compared to manual systems. The Arduino-based automatic overhead crane design succeeded in meeting the research objectives, increasing work efficiency and safety. Routine maintenance and periodic checks on mechanical and electronic components need to be carried out to ensure the system continues to function optimally and reduces the risk of damage.

Traffic congestion and limited parking spaces in the tourist area of Jalan Braga, Bandung City, have become significant issues that require innovative solutions. This study aims to design and implement a Smart Parking System using Internet of Things (IoT) technology and a mobile application to enhance efficiency, transparency, and convenience in parking management. The system is designed to detect real-time parking availability using ultrasonic sensors integrated with microcontrollers, and deliver this information to users through an Android-based application. Additionally, the system features parking slot reservation, digital payment, and parking data management for operators. Test results show that the system can reduce the time needed to find parking by up to 40% and increase user satisfaction. The implementation of the Smart Parking System in Jalan Braga is expected to support smarter and more environmentally friendly urban mobility in Bandung City.

The increase in online buying and selling due to government appeals during the Covid-19 pandemic has created a new habit in society, which also serves to reduce physical contact and prevent the spread of the virus. However, with the increase in delivery of goods, challenges arise in maintaining the cleanliness and safety of received packages. To address this, a smart package receiving system was developed that features automatic sterilization using ultraviolet (UV) lights and disinfectant spraying on incoming packages. This system aims to prevent the transmission of viruses that may be attached to the package. In addition, the system helps monitor and secure packages, especially when the owner is not at home. The system uses a microcontroller as the control center, equipped with an ESP32-CAM camera to document photos of the sender, as well as an ultrasonic sensor to detect whether the package is in the box or not. The process starts when the courier presses the “there is a package” button, which sends an OTP code to the receiver's Telegram. The courier enters the OTP code, places the package in the box, and closes it. After that, the UV lamp turns on for sterilization, the ESP32-CAM photographs the package, and the ultrasonic sensor detects the package status. If the package is detected, a photo notification of the sender is sent to Telegram, informing the recipient that the package is ready for pickup.  

Floods are natural disasters that often occur in Indonesia and cause damage to property, infrastructure, and casualties. One of the main factors causing flooding is the failure of water management systems such as reservoirs to manage the sudden increase in water volume. This research aims to design an automatic reservoir sluice controller by utilizing Internet of Things (IoT) technology to reduce flood risk. The system uses a NodeMCU ESP8266 microcontroller and an HC-SR04 ultrasonic sensor to monitor the water level in real-time, as well as a servo motor that controls the sluices. The system is connected to the Blynk app, allowing remote monitoring and control of the sluice gates via mobile devices. This tool automatically adjusts the position of the sluice gate based on sensor data to keep the water level safe and reduce the potential for flooding. The test results show that this IoT-based automated system is able to work effectively in controlling sluice gates and can be used for flood disaster prevention in the surrounding environment.

In the digital era, online buying and selling transactions are increasing, so that shipping services have an important role. However, there are various problems in package delivery, such as loss or damage due to the absence of the recipient at the location. This study aims to design and build an IoT-based Smart Box that allows safe package receipt. This system is equipped with a keypad, ultrasonic sensor, load cell sensor, and ESP32-CAM for automatic image capture and sending notifications to users via Telegram. Tests were carried out on various aspects of the system, including sensors, IoT connectivity, and package storage security. The test results show that the tool can function well in securing packages and providing real-time notifications to recipients.