Integrating the proposed workflow with other technologies, such as computer vision-based quality grading, can create a comprehensive automated system for agarwood processing. By incorporating computer vision algorithms for quality assessment, the system can analyze various visual attributes of the agarwood, such as resin color, texture, and shape, to determine its grade. This information can be used to optimize the resin extraction process by prioritizing high-quality agarwood for extraction. Furthermore, implementing real-time monitoring and feedback mechanisms can enable the system to adjust extraction parameters based on the quality assessment results, ensuring consistent and efficient production. Additionally, integrating IoT devices for data collection and analysis can provide valuable insights into process optimization and quality control. By combining these technologies, the automated system can streamline the agarwood processing workflow, improve efficiency, and enhance the overall quality of the extracted resin.