Python-based application development with vision-based sensors: Develop an application using OAK-D camera with safety algorithm. The system automatically moves robot to the safest area which farthest task location from human hand. A safety indicator is integrated to divide safety area between humans and robots. This research focuses on applying the system to e-waste disassembly management

Python-based application development with YOLO object detection: Designed an application that detects humans and objects, as well as calculates the distance between them. Integrated an LSTM algorithm to classify changes in human and object locations, predicting human motion. This motion prediction is then used to trigger robot speed control to prevent potential collisions when humans interact in the workspace.

Python-based application development with Mediapipe human skeleton detection: Designed an application that detects human skeletons using Mediapipe. By calculating the Euclidean distance and calibrating human distance with the camera, the application accurately determines the human's proximity. Based on ISO/TS 10566 standards, the system adjusts robot speed according to human presence in the workspace, enabling full speed, reduced speed, or a complete stop to ensure safe interaction.

Website-based application development using HTML and JavaScript: Designed a virtual laboratory application for managing teaching resources in an Analog Electronics course. Integrated Firebase as the database to schedule student access to laboratory computers. The application supports distance learning, providing a flexible solution during the pandemic.

Website-based application design with Wemos D1 for IoT devices: Developed an ultrasonic sensor monitoring application to detect and monitor coral reef conditions. The application includes data logging and mapping features to track and visualize reef health. This system serves as a prototype for environmental monitoring using IoT technology.