Real-time Classification of Vehicle Logos on Arduino Nano BLE using Edge Impulse

Vehicle logo acquisition or recognition has been a popular study field in intelligent traffic system for the latest decade. In this paper, a real-time vehicle logo recognition or classification method based on Convolutional Neural Network (CNN) using Edge Impulse is introduced. Arduino Nano 33 BLE coupled with an OV7675 Camera module has been used for the implementation of the algorithm. Edge Impulse has been used for training, testing and validation of the Convolutional Neural Network model. The images are taken by the camera attached and sends them to the model which classifies the images and displays the results on the serial monitor. This will helps in real time applications to identify the vehicle logos or to classify the vehicle logos using CNN model.