Hydrological monitoring station image identification monitoring system based on edge intelligence
An image recognition and monitoring system technology, applied in transmission systems, character and pattern recognition, instruments, etc., can solve the problems of lack of objectivity, misjudgment safety, inability to monitor the whole process, etc., to achieve effective and reliable transmission, low latency, convenience Monitoring the effect
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[0041] Embodiment 1: An image recognition monitoring system for a hydrological monitoring station based on edge intelligence, such as figure 1 shown, including smart cameras, edge nodes, macro base stations, smart mobile terminals, cloud centers, and visualization centers.
[0042] The output end of the smart camera is electrically connected with the input end of the edge node, the output end of the edge node is electrically connected with the input end of the macro base station, and the output end of the macro base station is electrically connected with the input end of the cloud center. The terminals are electrically connected together, and the output terminal of the cloud center and the input terminal of the visualization center are electrically connected together.
[0043] The output end of the macro base station is electrically connected with the intelligent mobile terminal.
Example Embodiment
[0044] Embodiment 2: On the basis of Embodiment 1, please refer to Figure 2-Figure 4 , a CDN main server is arranged outside the intelligent mobile terminal, the output end of the intelligent mobile terminal is electrically connected with the input end of the edge node, and the output end of the edge node is electrically connected with the input end of the CDN main server Together, the output end of the CDN main server is electrically connected with the input end of the cloud center.
[0045] The intelligent camera is composed of a camera, a development board and an edge computing system, and the camera adopts a camera with a focal length of more than 6mm to meet the monitoring effect of longer distances;
[0046] The development board is developed with Raspberry Pi 4B (Raspberry Pi). The main hardware parameters of Raspberry Pi 4B are as follows: 1.5GHz quad-core 64-bit ARM Cortex-A72 chip, LPDDR4 SDRAM memory, choose 8GB, onboard full-duplex thousand Mega Ethernet port, on...
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