Machine vision is growing rapidly. How to find practical application scenarios?

The second trend is human-machine collaboration and data flow. In the past two years, AGV has been widely used in factories, which is a typical scenario of human-machine collaboration. First of all, machines do not completely replace manual labor. Some mechanical and repetitive work is done by machines to achieve harmonious coexistence between people and machines. In the past, only goods were moved in factories, and data did not flow. After being realized by machines, goods and data can flow at the same time, which is convenient for the cloud center to command and dispatch.

The third trend is that all data will be managed and mined after entering the cloud. "Data itself has no value. The value generated after data collision is the greatest." Cai Hua believes that the final collision and mining must come from the business end. Taking the application of AGV as an example, the flow of data can find the rules, discover the machine's running track, operation times, etc., and dig out the key to improving the efficiency of business processes, thereby comprehensively improving the efficiency of the entire factory.

Which industrial application scenarios have great prospects?

Cai Hua believes that the first is logistics, including traditional express delivery, e-commerce logistics, production content logistics, contract logistics, etc. There are many new opportunities in this area as the market develops and changes.

Take the changes in offline retail warehouses as an example. In the process of fighting against online shopping, large supermarkets have gradually shifted to convenience stores based on communities and families. In this process, the biggest change is not the sales of goods at the front end, but the change in the flow of goods. Orders are becoming more and more scattered, and goods need to be broken down after entering the warehouse. At this time, the content that the warehouse can improve becomes more important, and it requires an automated process to achieve.

For express logistics, the logic is basically that of an unmanned warehouse. For example, hundreds of robots are constantly moving and carrying goods on a platform of several thousand square meters, performing tasks such as warehousing and sorting. This further demonstrates the superiority of the scheduling algorithm.

The second is 3C manufacturing, a typical example is mobile phone manufacturing, including PCB, handset, microphone, button, screen, module, battery, etc.), which requires a lot of production and intelligent testing. The degree of automation in production is already very high, which improves efficiency and yield rate.

Cai Hua said that the reason why China has developed rapidly in the above aspects is that there is no shortage of scenarios. There are too many application scenarios for learning, practicing and even trial and error, which provides a good soil for growth. Hikvision hopes to empower intelligent manufacturing through AI, and gradually apply artificial intelligence technologies such as deep learning and Internet of Things technologies to the field of intelligent manufacturing, from machine vision systems that complete multi-dimensional perception, data collection and processing to mobile robot systems that realize intelligent internal logistics, and continue to promote machine intelligence, service intelligence, and production intelligence.