The detection of hazardous gases, such as carbon monoxide (CO), is crucial for ensuring human safety and health, especially in enclosed environments or areas with a high potential for exposure to toxic gases. Carbon monoxide is a colorless, odorless gas that is extremely dangerous when inhaled in large amounts. Therefore, a CO detection system that can provide early warnings is essential. This research aims to design a carbon monoxide (CO) detector using the MQ-7 sensor, which can detect CO concentrations in the air. The detection system is developed based on Internet of Things (IoT) technology, enabling real-time CO detection data to be transmitted to a cloud platform or user devices via an internet connection. This allows users to monitor CO levels in their environment anytime and anywhere. The system consists of the MQ-7 sensor to detect CO levels, a microcontroller as the controller, and a communication module to send data to the internet. The main advantage of this system is its ability to notify users if CO levels exceed a safe threshold. Thus, this detector can function as a preventive tool against CO exposure accidents. The use of IoT in this system also facilitates remote monitoring, improving the effectiveness and efficiency of managing a safe environment.

This study aims to design and develop a GPS tracking system for ships integrated with Internet of Things (IoT) technology. The system enables real-time ship position monitoring via the Telegram application by utilizing ESP32, SIM800L, and GPS Neo 6M modules. The research employs an experimental method with both static and dynamic testing of hardware components such as GPS modules, SD cards, and battery performance. The test results demonstrate that the system successfully transmits accurate coordinate data to Telegram and logs the location on the SD card module. This system is expected to serve as an alternative solution to improve ship tracking security and efficiency, particularly in emergency situations or AIS signal loss.

Unloading equipment is equipment used to assist the process of loading or unloading cargo, such as cargo or bulk cargo from transportation facilities. One example is a conveyor, a mechanical system that can move goods. However, damage often occurs to the conveyor, so an Arduino Mega-based safety device was designed to fulfill the safety aspect. The aim of this research is to find out how to design an Arduino Mega-based safety device system for conveyor unloading equipment using the Research and Development (R&D) method. Using 2 types of testing, namely: static and dynamic testing. Arduino MEGA works fine. If the motor rotates and the conveyor moves, the conveyor is said to be working properly. The safety device on the Arduino Mega-based conveyor was made using Arduino IDE software using the C++ programming language. This safety device is able to secure the conveyor when damage occurs by cutting off the electricity when there is an overload on one of the conveyors so that the entire conveyor stops working. The conveyor series consists of a power supply, box panel, and three conveyors. After the tool has been tested and can work well, the testing is complete and the tool is ready to be used.

Along with the development of the industrial sector, companies are competing to create quality and affordable products. To support production, automation tools have emerged that help the production process so that it is faster. One of the machines that is widely used by large factories is a 3-phase induction motor. 3-phase induction motors are often used in driving equipment in industry because they have a simple construction, are relatively cheap, lightweight, have high efficiency, and are easy to maintain. This study utilizes the A3114 hall effect sensor device, PZEM-PP4T Sensor, 20x4 LCD, ESP32 module, Relay, Mitsubishi D700, MCP 4725 Sensor. The tests carried out showed that the performance of the sensor for measuring speed, voltage, and current on 3-phase motors has a high level of accuracy. Testing of motor speed shows a difference in speed value (Rpm) between the hall effect sensor and the tachometer, with an average accuracy percentage of 4,12%, indicating that the hall effect sensor has a fairly good level of accuracy. For voltage measurement, the Pzem sensor compared to the Multitester produces an average accuracy percentage of 0,90%, indicating that the pzem sensor is very reliable. Meanwhile, current testing shows a difference in value between the pzem sensor and the multitester with an average accuracy percentage of 0,98%, indicating a fairly high level of accuracy. Overall, this system can be relied on for measuring operational parameters of 3-phase motors because it has consistent and good accuracy. With this research, the 3-phase induction motor monitoring system which was originally done manually has changed to automatic and has a fairly high level of work efficiency.