Abstract

The industrial Internet of Things (IIoT) environment involves multiple production items, such as robots and automated guided vehicles (AGVs), among others. The practical industrial scenario requires communication of production items while also considering mobile recognition and positioning. Hence the perception approach requires not only combining communications but also realizing the recognition and positioning of multiple communication cells. This Letter proposes a multi-optical cell recognition and positioning framework based on LED image features. The LED images are obtained by a CMOS image sensor. This framework utilizes convolutional neural networks (CNN) to train LED images for recognition between multiple optical cells and locates precise positions through region recognition within the optical cells. The experimental results show that the mean accuracy of the CNN model for two LED cells is above 99%, and the mean accuracy of region recognition within the optical cell is as high as 100%, which is significantly better than other traditional recognition algorithms. Therefore, the proposed framework can provide location-aware services for visible light communication and has a wide application prospect in IIoT.

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