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The purpose of this paper is to introduce a system that uses the combination of working aid blind techniques to help blind people to have better navigation against objects, also to be aware of road and traffic lights signs using real-time image-processing. This study aims at improving the processing speed of object detection by introducing the latest Raspberry Pi 4 module, which is more powerful than the previous versions. As a result, the Single-Shot Multibox Detector MobileNet v2 convolutional neural network on Raspberry Pi 4 using TensorFlow Lite 2, is employed for object detection. A model called SSD MobileNet v2 320x320, which is trained on the COCO dataset from the TensorFlow model zoo, which is used in this system. Also, the traffic light signs classification is achieved via machine learning techniques. With all modules attached on the hat, video frames captured from the piCamera module are analyzed and searched for

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