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Application of Zig Bee Wireless Communication Technology Combined with Intelligent SLIC-CNN Model in Mineral Geological Exploration
Deming Zhang, Zhensheng Fan, Meng Zhao, Qingyu Yin, Maozheng Zhan, Jun Zhao, Hang Zhou and Gonghao Dong

High-resolution Geological Mapping (GM) greatly aids mineral geological exploration. Despite this progress, several challenges remain in high-resolution GM. The subjective vision of line segments, instruments, and field measurements creates high- resolution GM. The fieldwork is often restricted by climate, topography, and manpower, and there is room for improvement in how things get done. In addition, Unmanned Aerial Vehicles-UAVs’ expanding capabilities have been used in a wide range of contexts. Creating a system of communication between the planes to facilitate the free flow of data is crucial to the success of this system. Since ZigBee is a promising medium for UAV communication networks, we choose to adopt it. Employing the “ZigBee module and the Simple Linear Iterative Clustering-Convolutional Neural Network (SLIC-CNN)” technique, this research presents for GMs. The suggested technique is known as ZigBee-SLIC-CNN. Here, we acquire high-resolution remote sensing photos using UAV, work with some fundamental preparation to establish the lithology, and then perform most of the mappings using high-resolution spatial information. The system’s automatic mapping method is founded on the SLIC-CNN algorithm and brings in a substantial amount of previously performed fieldwork. To analyze the images and verify the lithologic distribution, CNN is employed; the SLIC methodology is used to create the rock’s boundary and contact interface, and the mode and expert judgement method describes the mapping and fusion results. The proposed technique’s AUC in this research achieved 0.942. k = 0.863 was the Kappa test result, and a detailed geological description was developed. The effectiveness of the proposed strategy in mineral geological exploration is demonstrated by analyzing its performance and comparing it to other existing approaches.

Keywords: Mineral geological exploration, GM, Unmanned Aerial Vehicle (UAV), ZigBee, SLIC-CNN