First of all, from the long-term entrustment of financial institutions, our technology is leading, so that we can respond quickly. The whole data link can form a data model to support financial data management, which will be discussed later.

This is the three-dimensional service I just mentioned, including manual service, Internet of Things technical service, monitoring service, warehousing service and big data service.

Firstly, it is divided into four parts from the technical equipment of the Internet of Things. PDA+ RF technology, which has been fully radiated, is bound with convergence through some RF technologies to stipulate business risks.

The second device is OBD technology. We can say that there are not many companies in the whole industry that can achieve more than 40%, but this piece of technology can achieve a one-time recognition rate of more than 85%. The delayed upload rate of the whole data is 0, which exceeds the capability of the hardware itself and combines some core algorithms in the Internet of Things.

The third terminal combines the Bluetooth technology of OBD, which can meet some monitoring requirements. The last one is exclusive APP+ optical recognition, and each shot is recognized.

The second mode is patrol supervision+technology, which is mainly composed of the financial company of the manufacturer, and can also be used for the management of the second network with controllable cost. We have cooperation with some used car companies, and we can communicate if we want. This piece, coupled with the technology of Internet of Things, dynamic control is still very effective.

The third part is the warehousing supervision mode+technology. We can put some financing tools in the city center. This model reflects whether a warehouse monitoring company has achieved effective distribution. We also made a demonstration here. Changjiu Group will set up a city center library in a first-class city at the end of next year. The principle of setting is very simple, 200 kilometers for three hours. We also cooperate with several factories in this field from the source.

I want to mention big data, because we have been doing business for more than ten years. From the whole decade, there are more than 100 dealers in the sample, which has the basis for us to integrate data. Several data models, one is an explicit data model, and there are some invisible data models to be discussed later. There are many financial companies today, so I will make a score on the leading mode of risk first, and we will make a basic score on which banks and regions are prone to risks. Secondly, we will make a business score, according to the number, time, investment scale of the city where the dealers are located, and the distribution under their dealer brands. We will give a comprehensive score. This piece comes from years of management experience.

Finally, after doing the practice, make a risk score, such as whether there is early warning information, wage arrears and other information. Put this part together and give it some score distribution. As I said in the last meeting, we have started to test the visual model. Under normal circumstances, it should be handed over to financial institutions for trial next month. This paper can be used to check the branches of financial institutions, or to detect brands and predict some risks. We can also customize the reporting service according to some manufacturers.