## 5 Conclusions  
In this paper, we propose a blockchain-based trusted data management and trading platform for the IoT. After analyzing the credibility of the platform, the data provider, and the data provider's autonomy to the data in the traditional data management mode of the IoT, we consider two kinds of transactions, namely payment transactions and storage transactions, and realize the up-chain and trusted transaction of the IoT data by utilizing the characteristics of blockchain. At the same time, in order to improve the transaction automation and efficiency, we designed a smart contract to complete this process. Finally, we implemented the proposed system.  
While the results in the experimental test show positive results, in the actual IoT data flow scenario the participating transactions do not belong to the same network environment, so the time to reach consensus on the blockchain will increase. At the same time, our tests of the system were evaluated with a small number of nodes. In a real-world scenario, the number of nodes participating in the blockchain would be higher, which would increase the data processing burden on each node and reduce performance. In the process of running the blockchain system, it may face the problem of increased demand, so it is also necessary to consider the problem of system scalability and update the version in a more convenient way.  
In terms of system scalability, we have layered the system, and scalability can be deployed at the application layer in the form of plug-ins. At the same time, our blockchain platform is modified with reference to the source code of Bitcoin, and relevant data structures can be flexibly modified to adapt to more needs. In the future, we will make various functions of the blockchain into APIs, and the application layer only needs to use these APIs to achieve good scalability.  
Future works can be improved in the following ways:  
1. The experiment in this article was conducted on a single machine and multiple nodes. In the future, we will consider using clusters or edge computing services for deployment to further verify the performance of the system.
2. In the future, more physical equipment can be used to test the reliability and throughput of the system.
3. Future research can try to improve scalability and support more IoT application integration. At the same time, the content of our blockchain platform is modifiable, which means we can expand more services at the application layer through plug-ins.
4. Future research can consider adding a federated learning framework to deal with the distributed training scenarios of large-scale IoT data and achieve this expansion by dividing the roles of nodes in the blockchain system.  
Conceptualization, Z.Y. and Y.L.; methodology, Z.Y., Y.L. and X.J.; validation, Z.Y. and Y.L.; writing--original draft preparation, Z.Y.; writing--review and editing, X.J., X.L., Y.X. and M.L.; supervision, Y.L., X.J. and X.L.; project administration, Y.L., X.J., X.L., P.C., B.T. and B.L.; funding acquisition, Y.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China (Grant Nos. 62302317 and 62302316), Shenzhen Colleges and Universities Stable Support Program (Grant Nos. 20220715183602001 and 20231122005530001), Shenzhen Science and Technology Program (Grant No. RCBS20221008093227027), Natural Science Foundation of Top Talent of SZTU (Grant No. GDRC202319), and SZTU Project No. 20224027010006.  
Not applicable.  
**Data Availability Statement:** Dataset available on request from the authors. The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.