Served as an internship mentor, leading 2 project members to build a machine learning model of License Plate Recognition System and implementing access control framework. Initially, we collected license plate dataset with labels and trained one CNN model for locating plates and another RNN model to recognize plate numbers. Then, we developed Flask APIs to receive video frames from web cams, calculating edit distance as similarity between predicted plate numbers and those from company database. Finally, we could control the entrance gate by checking whether the vehicle owner is our employee. Our system’s prediction accuracy reached 90% in the examination.