Face recognition technology is widely used in security, business, finance and other fields. In view of the high cost and low ease of use of existing face recognition systems, a scheme based on Raspberry Pi for face recognition is proposed. First, the Harr cascade method is adopted in the OpenCV computer vision library to locate the faces in images. Then the improved MobileNetV2 model is employed to extract and classify the faces to obtain an optimized face recognition model. Finally, the model is ported to Raspberry Pi for face recognition. The model has an accuracy of 95% for people in the gallery while 80% for strangers. Experimental results show that the system remains stable in face recognition, with fast recognition speed and wide application scenarios.