Forest smoke and fire real-time monitoring system and method based on robust multi-view
A real-time monitoring system and multi-view technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of lack of scalability and low accuracy of forest fire monitoring
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Embodiment 1
[0091] The forest fireworks real-time monitoring system based on the robust multi-view of the present embodiment includes:
[0092] Forest pyrotechnics data acquisition module, used for real-time collection of forest pyrotechnics data;
[0093] The data transmission module is used to transmit the forest pyrotechnics data collected in real time to the background server;
[0094] Robust multi-view detection module, located in the background server, is used to detect forest pyrotechnic data, so as to determine whether there is a pyrotechnic accident in the forest;
[0095] The working principle of the system: first, the forest pyrotechnic data collection module collects the forest pyrotechnic data in real time, then the data transmission module transmits the real-time collected forest pyrotechnic data to the background server, and finally the robust multi-view detection module detects the forest pyrotechnic data, thereby Determine whether there is a firework accident in the fore...
Embodiment 2
[0098] The forest fireworks real-time monitoring system based on the robust multi-view of this embodiment is based on embodiment 1, wherein the data transmission module can adopt the Zigbee transmission protocol, specifically: in several forest fireworks image data collectors evenly arranged in the forest Set the Zigbee transmission protocol related sensors, set the Zigbee transmission protocol on the background server at the same time, and connect the two through the Zigbee transmission protocol wireless communication.
Embodiment 3
[0100] The forest fireworks real-time monitoring system based on robust multi-view of this embodiment is based on embodiment 2, wherein the robust multi-view detection module is located in the background server, and the method for establishing the robust multi-view detection module specifically includes the following steps:
[0101] Firstly, the initial robust multi-view detection model is established; then the parameters of the robust multi-view detection model are solved, that is, the final classification plane is solved; finally, the robust multi-view detection model is verified experimentally.
[0102] The aforementioned establishment of an initial robust multi-view detection model specifically includes the following steps:
[0103] S11, first obtain a sample data set, the sample data set includes a training set and a test set, after the sample data set is input to the robust multi-view detection model, it is processed into a multi-view data set, the multi-view data set use...
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