In recent years, with the continuous deepening of digital transformation in various industries, people can increasingly feel that the era of digital intelligence is accelerating towards us.
Digital cutting-edge technology represented by 5G, cloud computing, edge computing, big data, and artificial intelligence has been deeply integrated with the industry and incubated a large number of innovative application scenarios. These scenarios not only change the industry's processes and procedures, but also disrupt business models and reconstruct the industrial ecosystem.

The most typical one is the industrial manufacturing industry, which has always been known as the pillar industry of the national economy.
As is well known, industry is the most important material production sector and a symbol of national strength. It not only provides necessary consumer goods for people's material life, but also provides raw materials and power for the development of the entire society, supporting the country's economic independence, political independence, and national defense security.
Throughout modern human history since the 18th century, it is actually the development history of the Industrial Revolution. Starting from the steam engine, humanity has undergone three industrial revolutions before achieving a leap in productivity and gradually entering the current information age.

Nowadays, the integration of digital technology and industrial technology upgrading will give rise to the fourth industrial revolution. How will this revolution reshape the operational mode of human society? What direction will AIoT+Industry 4.0 develop towards?
Everyone can follow this article to gain a deeper understanding of the future scenarios of digital manufacturing.

AIoT， How to empower industrial manufacturing

Everyone should have some understanding of the Fourth Industrial Revolution. This is an industrial revolution with breakthroughs in artificial intelligence, virtual reality, graphene, genetic technology, quantum information, controllable nuclear fusion, clean energy, and biotechnology.
From the perspective of industrial manufacturing, its biggest change is the in-depth application of digital intelligence technology and the introduction of Industrial Internet.

Industrial Internet is totally different from the mobile Internet (consumer Internet) we use every day. It is the representative of the industry Internet and the deep integration of the new generation ICT (information communication) technology and OT (industrial operation) technology.
Industrial Internet is not only the digital upgrading of industrial infrastructure, but also the evolution of industrial processes and industrial economic ecology. Through the comprehensive connection of industrial Internet to people, machines, things, systems, etc., a new manufacturing and service system covering the whole industry chain and the whole value chain can be built. This system is based on informatization, networking, and intelligence. Its driving force, in addition to fossil fuels and electricity, also includes computing power and connectivity.
With the help of computing power and connectivity, industrial manufacturing division of labor and collaboration will be further refined, and production processes will be deeply optimized. The research and development, production, quality control, and maintenance processes in the production process will be manually controlled and replaced by computational control. The ultimate manifestation of computing power is AI artificial intelligence.

After speaking for a long time, people may find it too abstract and difficult to understand. Next, let's take a look at several cases to see how digital intelligence empowers industrial manufacturing and improves production efficiency.
Firstly, let's take a case study of intelligent sorting of industrial robots on an assembly line.
After entering the 21st century, industrial robots and robotic arms have been widely adopted, replacing some assembly line workers. Early robots could only accept specific instructions and programs, perform a small number of fixed operations, and lacked intelligence.
When different items are delivered by the conveyor belt, the robot cannot make category judgments on the items, let alone differentiate them.
After the introduction of the Industrial Internet, the situation is different.
By installing a communication module on the robot, the object images captured by the robot camera can be uploaded to the cloud for image recognition. Combining machine learning and artificial intelligence algorithms, the object category can be determined in advance. Then, under the instructions from the cloud, the robot drives the robotic arm to grab items at accurate positions and classify them.

In this way, robots have truly achieved the same processing power as assembly line workers, or even stronger.
Let's take a look at another case - product quality inspection combined with AIoT technology.
Product quality inspection has always been a challenge for automated intervention in the past. Due to the numerous issues with product defects and the varying locations and forms of damage, traditional automated machinery is unable to make accurate judgments and can only rely on manual identification and judgment.
Now, with the help of data collection devices such as cameras and sensors, it is possible to take high-speed photos of the inspection object and then send the data to the cloud. Combining cloud computing with machine learning, identify defect categories such as virtual soldering, solder leakage, corrosion, fracture, etc., and then instruct the robotic arm to identify and pick out defective products.

What's even more impressive is that AI can not only identify product defects, but also summarize defect patterns, helping production lines find possible causes of defects and make corrections to avoid them.

Analysis of Core Elements of AIoT

From the above two examples, we can see that achieving true digital intelligence requires several important elements:

Firstly, it is necessary to have powerful data acquisition equipment, including ultra-high resolution cameras, ultra-fine precision sensors, and so on. Data collection devices are the source of data. Without data, we have never discussed it.
Secondly, we need high-performance and ubiquitous communication networks.
A complete network, including terminals and network side devices. The module determines the network performance on the terminal side.
In recent years, with the development of the times, wireless communication technology has significantly caught up with the gap in communication capabilities compared to wired communication technology. Moreover, wireless technology itself has the advantages of flexible deployment and wireless coverage, so it is widely used in industrial manufacturing, logistics and transportation, education and healthcare, and urban governance.
The capability of wireless modules is also advancing rapidly, with power consumption continuously decreasing and integration increasing. Often, one module can support multiple formats and functions. For example, the Rx500x series module of Mobile Remote Communication not only supports 2/3/4/5G, but also provides GNSS positioning, eSIM and other functions.

5G， It is currently the most advanced communication technology. It has the characteristics of high bandwidth, low latency, and massive connections, making it very suitable for industrial manufacturing scenarios. The high-speed image recognition and transmission of massive high-definition images mentioned in our previous case require high-speed networks such as 5G.
And in order to quickly achieve a closed loop of photography, analysis, and processing, the network needs to have extremely low latency, which is also a strength of 5G. The end-to-end latency of 5G air interface can be controlled within a few milliseconds, with low jitter and high reliability, fully meeting the requirements of industrial scenarios.
After the 3GPP R16 standard was established, 5G industrial modules are constantly emerging, empowering the 5G transformation of industrial scenarios.
Finally, there is a powerful computing platform.

With the help of modules and networks, data can flow smoothly and enter the cloud. By combining cloud computing with big data analysis, massive IoT data can be processed. By building appropriate algorithm models on this data, intelligent production processes can be achieved, replacing manual labor with efficient AI, improving efficiency, and reducing costs.
It is worth mentioning that the application of AI computing power can be completed not only in the cloud computing center, but also in the edge computing node, and even directly on the communication module with AIoT capability.
In the era of digital intelligence, communication modules not only have strong communication capabilities, but their computing power is also constantly increasing, and they can undertake more and more end computing tasks, including the operation of artificial intelligence algorithms.
For example, the intelligent modules SG500Q, SA800U, SC66, SC665S and other products of Mobile Remote Communication have basic AI computing power, integrating high computing power CPUs, high-performance GPUs and NPUs, which can complete a lot of computing work and share the pressure of the cloud.

The combination of end computing, edge computing and cloud computing has realized the ubiquity of computing power, which not only effectively reduces the load of network transmission data, but also reduces the delay of data processing.

Conclusion

What is the most precious thing in the era of digital intelligence?
It's imagination.
Our society has hundreds of industries, each with its own work scenarios. Digital intelligence technology is a form of empowerment, and how to use this empowerment to deeply transform the industry in which one operates is a question that everyone in the industry must deeply consider.
From the perspective of industrial manufacturing alone, various digital applications that have emerged are already subtly disrupting our industry - in smart mines, unmanned mining machines and mining cars are systematically excavating and transporting ores; At the smart dock, staff members in comfortable air-conditioned rooms are remotely operating cranes to transport containers; In the smart grid, unmanned inspection robots are conducting strict inspections on power transmission and distribution equipment
Quantitative change leads to qualitative change, and the evolution of countless segmented scenarios ultimately drives industrial transformation.
The future has arrived, let's wait and see.

This article is reprinted from Tencent website：https://new.qq.com/omn/20210902/20210902A0A1K100.html。