People with visual impairments face numerous challenges when interacting with their environment. Our objective is to develop a device that facilitates communication between individuals with visual impairments and their surroundings. The device will convert visual information into auditory feedback, enabling users to understand their environment in a way that suits their sensory needs. Initially, an object detection model is selected from existing machine learning models based on its accuracy and cost considerations, including time and power consumption. The chosen model is then implemented on a Raspberry Pi, which is connected to a specifically designed tactile device. When the device is touched at a specific position, it provides an audio signal that communicates the identification of the object present in the scene at that corresponding position to the visually impaired individual. Conducted tests have demonstrated the effectiveness of this device in scene understanding, encompassing static or dynamic objects, as well as screen contents such as TVs, computers, and mobile phones.

翻译：视障人士在与环境互动时面临诸多挑战。我们的目标是开发一种能够促进视障人士与周围环境沟通的设备。该设备将视觉信息转化为听觉反馈，使使用者能够以符合其感官需求的方式理解所处环境。首先，根据准确性和成本考量（包括时间和功耗）从现有机器学习模型中选择物体检测模型。随后将选定模型部署于连接专用触觉设备的树莓派上。当使用者触摸设备特定位置时，设备会发出音频信号，向视障人士传达该位置对应场景中存在的物体信息。测试结果表明，该设备在场景理解方面具有有效性，能识别静态或动态物体，以及电视、电脑、手机等屏幕内容。