The phenomenon that occurs in the load lifting system is the need for an efficient and reliable mechanism to move the crane hoist pulley vertically and horizontally. This study aims to design and test a crane hoist system that uses a DC motor and a stepper motor controlled by an L293D motor driver, and to develop an application based on MIT App Inventor to control the movement of the motor. The research method used is integrated hardware and software design, followed by testing the performance of the motor, driver, and the application developed. Testing was carried out under limited load conditions, to measure the motor speed, voltage, and current used at loads of 10 to 100 grams. The results of the study showed that the system can function well at varying speeds, and the motor is able to lift a maximum load of up to 100 grams with a speed that decreases according to the weight of the load. The MIT App Inventor application successfully controls the motor effectively via a WiFi connection with a maximum distance of 10 meters, and loads the operation of the crane vertically and horizontally. This study proves that the designed system is able to work optimally in lifting and moving loads, and the application developed provides easy and efficient control.

Main engine is the main driving engine. This research develops a ship's main engine temperature monitoring system using the Blynk application. Thermocouple sensors measure engine temperature and IR Sensor measure RPM, the data is processed by ESP32, and sent to the Blynk cloud server, this research aims to determine the design of a prototype intelligent monitoring system to detect the temperature of a ship's main engine using a Thermocouple sensor, NodeMCU ESP32 which operates at 3.3V power is used as the processing core data. The system design in this research integrates Internet of Things (IoT) technology. Test factors for thermocouple temperature measuring devices and RPM sensors (IR Sensors). The test procedure uses a dynamo as a simulation of the main engine, tested for 5-10 minutes under normal conditions and 5 minutes when the dynamo feels warm to hot.

Most door accesses used in homes still use conventional keys. Where the use of manual keys is still vulnerable to loss or damage and is not very safe to use, because manual keys can be duplicated or duplicated by other people. This certainly feels less practical and flexible. This research aims to help improve door security. With a voice recognition system, only certain people can access it using a certain access code. Researchers used the trial and error method. The factor being tried is the voice recognition V3 module which can read voice recordings. The results of this research can be implemented in the form of a tool, where the system can open and close house doors according to the planned design, namely through voice commands and the designed system can run normally according to the automatic system that has been designed in prototype form. The conclusion from this research is that the voice recognition module is capable of recording sounds up to a distance of 20 cm. In voice recording < 10 cm the module is relatively easier to receive voice commands, in recording > 10 cm and < 15 cm the module is slightly less able to receive voice commands, so that in voice recording at a distance of 15 cm to 20 cm the module is very poor in receiving commands sound well.

The Unmanned ships have become a primary focus in maritime technology development to enhance efficiency and navigational safety in waters. In this research, a unmanned ship utilizing ESP32CAM as its core system is designed to detect navigation lights of other vessels and avoid potential collisions. The initial response of the ESP32CAM camera reads the colors of lights approaching the unmanned ship within a distance of less than 100cm. The ESP32CAM reads and identifies colors through image processing. When the ESP32CAM detects green and red lights, it commands the buzzer to sound. The color detection system works such that when the ESP32CAM detects a red light, it sends a signal to the servo motor to move left, and when it detects a green light, it sends a signal to the servo motor to move right. The servo motor functions as the ship's rudder. Testing of the navigation light system with ESP32CAM camera to prevent ship collisions is conducted with predetermined scenarios, including testing with red LEDs, green LEDs, and overall system testing. The results show that the navigation light system with ESP32CAM camera functions well. The ESP32CAM camera can optimally identify light colors at a distance of 100cm. Based on the conducted research, the ESP32CAM camera is capable of reading both the distance and colors of lights as specified at a distance of 100cm.