A method and system for intelligent monitoring and management of a gmp workshop
A monitoring management and workshop technology, applied in the field of GMP workshop intelligent monitoring management method and system, can solve the problems of low intelligence
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Embodiment 1
[0027] like figure 1 As shown, the embodiment of the present application provides an intelligent monitoring and management method for a GMP workshop, wherein the method is applied to an intelligent monitoring and management system for a GMP workshop, and the system is communicatively connected with an intelligent camera device, and the method includes:
[0028] S100: Obtain a first image information set of the first GMP workshop through the intelligent camera device;
[0029]Specifically, the intelligent camera device is a device that performs all-round video monitoring of all angles of the first GMP workshop. Preferably, a plurality of intelligent camera devices are deployed in communication with the intelligent monitoring and management system of the GMP workshop. The location is set on the basis of comprehensive monitoring of the first GMP workshop, especially key areas such as vents and production lines; the first image information set of the first GMP workshop is the real...
Embodiment approach 1
[0046] The first collaborative system distributes the original model, that is, the first initial model, to each pharmaceutical factory, and each pharmaceutical factory conducts model training, and receives data from the first pharmaceutical factory, the second pharmaceutical factory, and the third pharmaceutical factory until the Kth pharmaceutical factory. The encryption result of the model parameters after the training is completed from the pharmaceutical factory, that is, the first encryption result is obtained. Because the key is distributed to K pharmaceutical factories by the first cooperation system, the first cooperation system has The authority to remove the mask, after removing the encryption masks of all the first encryption results, aggregate all model parameters to obtain the first encryption parameters, and then update the model through the first encryption parameters. The quantitative basis is relatively large, and the obtained analysis result of the first abnorm...
Embodiment approach 2
[0048] The first pharmaceutical factory, the second pharmaceutical factory, the third pharmaceutical factory, and the Kth pharmaceutical factory download the original model, that is, the first initial model, from the first collaboration system, and use multiple sets of the first personnel image information and all The first device image information trains the first initial model, until the first initial model reaches convergence, extracts model parameters and encrypts them, and sends them to the first collaboration system as the first encryption result. After the first cooperation system aggregates a plurality of information similar to the K training parameter model update completion information sent by the first pharmaceutical factory, that is, the update of the first abnormality identification model is completed, and when it needs to be called, it is sent to the first cooperation system. Request information, coordinate calls, and process data. The use of intelligent models c...
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