AI in Distribution: Determining Truck Loading completion percentage inside warehouses using image recognition algorithm

The project will focus to analyze those pictures algorithmically and let the management know how many cubic feet of a trailer is loaded after the loading procedure is completed. Therefore, management will be able to make the final decision before the trailers leave the distribution center. This project will make the decision-making more proactive than reactive. One of the major purposes of this project is to help the business to get more insights from the unstructured data to improve their operation and decision making. The author of the project will try to understand what percentage of the loading process is completed by analyzing the pictures. In the training dataset, we have already the completion percentage attached to different pictures. The algorithm will be trained to understand the target and feature variables. The target variable is the pictures here and the feature will come from the picture. As a result, the management will be able to understand what percentage of loading is completed for a certain trip. The author also wants to teach the operation team that there is enormous information hiding inside the unstructured data of the company.