Internet of Things system and service method based on joint learning

Abstract

The invention discloses an Internet of Things system and service method based on joint learning, and the system comprises an Internet of Things infrastructure, a cloud service platform, and a business application platform, the Internet of Things infrastructure is used for providing an infrastructure based on joint learning, training a target algorithm model based on a joint learning algorithm, and obtaining a target algorithm model; and processing the business demand acquired by the business application platform by using the trained target algorithm model, the cloud service platform is used for providing a basic general algorithm model based on joint learning, and selecting the basic general algorithm model according to the business requirements acquired by the business application platform; and the business application platform is used for acquiring a user business demand, receiving a processing result sent by the cloud service platform and feeding back the processing result to the user. Through joint learning and artificial intelligence, on the premise of ensuring data security, an AI technology ecology based on joint learning is created, so that data barriers of all parties are broken through, and industry ecology is broken through.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to an Internet of Things system and service method based on joint learning. Background technique [0002] With the development of Internet of Things technology and the increasing popularity of various Internet of Things IoT devices, the massive data generated by the IoT terminal in the future will soon exceed the data volume of the existing Internet. Edge and terminal intelligence are attracting more and more attention, and artificial intelligence technology can be effectively used to process data generated by massive devices. In recent years, the computing power of IoT devices has been continuously improved. In particular, AI chips dedicated to neural network computing have gradually become standard equipment for mid-to-high-end devices, and artificial intelligence has gradually migrated from the cloud to the terminal. Smart + is the trend of the future development ...

AI Technical Summary

Problems solved by technology

[0006] First, after cloudification, the degree of data centralization is too high, resulting in no guarantee of data security and increased risk of illegal data access;

[0007] The second is that the original application server is independent, but after the cloud system is installed, the security boundary of the application server is getting smaller and smaller, and even many loopholes will appear, and the protection mechanism still needs to be improved;

[0008] Third, from the perspective of application, the scope of digital applications is expanding, but security matching lags behind;

[0009] Fourth, the deployment of cloud computing is obviously dynamic, but the authorization is still static, which makes it difficult to match

[0010] (2) Data traffic processing is under pressure

[0012] (3) The "data island" has not yet been opened

[0013] On the one hand, due to the protection of user privacy and business secrets, and on the other hand, due to the differences in departmental business and development time, resulting in heterogeneous and simultaneous operation of multiple system platforms, system data is relatively independent, isolated, and data sharing cannot be realized, resulting in " Data isolated islands are not conducive to digital transformation applications, requiring a lot of time, energy, and cost to integrate resources

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