Underground Garage Patrol Based on Road Marking Recognition by Keras and Tensorflow

• Published in: Applied sciences Vol. 13; no. 4; p. 2385
• Main Authors: Gan, Jianwen, Zhang, Longqing, Chen, Hongming, Bai, Liping, Zhang, Xinwei, Yang, Lei, Zhang, Yanghong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2023
• Subjects: Algorithms; Artificial intelligence; autopilot; Cameras; Data entry; Embedded systems; Interfaces; Keras neural network; Libraries; Localization; Machine learning; Neural networks; Open source software; Remote control; Roads & highways; TensorFlow; Vehicles
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app13042385

The purpose of this study was to design an unmanned patrol service in combination with artificial intelligence technology to solve the problem of underground vehicle patrol. This design used the Raspberry Pi development board, L298N driver chip, Raspberry Pi camera, and other major hardware equipment to transform the remote control car. This design used Python as the programming language. By writing Python code, the car could be driven under the control of the computer keyboard and the camera was turned on for data collection. The Keras neural network library was used to quickly build a neural network model, the collected data was used to train the model, and the model was finally generated. The model was placed in the TensorFlow system for processing, and the car could travel in a preset track for unmanned driving.