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Since General Electric (GE) in the United States introduced the industrial Internet in 2012, it is most often compared to the consumer Internet. Although both are part of the Internet, they essentially engage in different types of business. As the name implies, consumer internet is consumer-centered, using Internet technology to connect various aspects of people’s lives such as shopping, entertainment, dining, and transportation. The data collected is then analyzed to enable further optimization, thereby improving transaction efficiency. The industrial Internet takes enterprises as its user base; it utilizes Internet technology, as well as industrial software and specialized information, to convert all aspects of an enterprise’s operations in areas such as production, management, and sales into digital data. Then, it employs new-generation information technologies such as Internet of Things and big data technologies to connect these various aspects together for optimization. It improves a company’s production efficiency, reduces costs, and helps the company unlock further potential. Due to the significant differences in the scale of the entities they are connected to, the technical requirements, security needs, and data processing demands for the operational equipment also vary greatly. Therefore, the demand for talents who can undertake and apply technology to ensure the proper operation of equipment also varies. In comparison, in the industrial Internet, factors such as the scale of device connectivity, security standards, technical complexity, and data processing requirements determine that this field has more stringent demands on professional technical talent. Firstly, their body of professional knowledge must cover research on core key technologies such as intelligent networks, industrial software and hardware, and CPS ； Secondly, a great deal of production experience is required, as well as proficiency in tools such as modeling and virtual simulation ； More importantly, it is necessary to be able to transform experience into models and possess comprehensive capabilities in big data analysis. So, what are the differences between consumer internet and industrial internet in terms of technology, security, data processing, and scale? Why do more experienced technical engineers being required for the latter, even though it also involves technical professionals? Consumer internet focuses on operations and user experience; compared to industrial internet, it is aimed at meeting consumers’ immediate needs for online purchases. Therefore, it possesses both media and industrial attributes. Media attributes: Composed of portal websites that primarily provide information, self-media, and social media. Industry category: An internet-based type that provides services for consumers in their daily lives, comprising e-commerce and online travel, among others. The combined use of these two attributes has enabled the internet, with consumption at its core, to rapidly penetrate every aspect of people’s lives, influencing and changing their ways of living. The business model of the consumer internet is typically based on the \"attention economy\" – that is, by providing high-quality content and useful information to generate data traffic, investors are attracted through the monetization of this traffic, thus forming a complete industrial chain. Therefore, in this era of \"information overload\" and \"scarce attention,\" how to obtain \"limited attention\" from \"infinite information\" has become the core challenge of the consumer internet. Thus, leveraging strong information and data processing capabilities, as well as the development of diverse mobile devices, many Internet entrepreneurs have begun to find ways to compete for attention resources. Centering around consumers, and using the provision of high-quality content and personalized entertainment as their main methods, they strive to attract attention quickly in a short period of time in order to generate traffic and achieve monetization. The key to such a consumer internet industry chain structure is to transform information technology into continuously evolving content delivery and innovative forms of consumer interaction. Novelty and interest are the keys to increasing user loyalty. Indeed, as relevant technologies continue to evolve, speech recognition has improved significantly, big data processing capabilities have seen substantial advances, and a vast array of applications are increasingly reaching individual consumers. From the diversified development of mobile applications to the rise of smart devices such as wearable gadgets, and further on to the advancements in cloud computing, big data, and artificial intelligence, the Internet is changing consumers’ behavior patterns, as well as transforming the ways in which businesses operate and provide services. The Internet era has begun to transition gradually from the \"small C era\" to the \"large B era\", marking the arrival of the industrial Internet era. However, when it comes to the integration of the mobile Internet with other industries, the technical requirements are not only higher and stricter, but also more complex. Taking the manufacturing industry as an example, the biggest feature of the industrial Internet in its integration with traditional enterprises is the shift from the traditional enterprise-oriented, scale-based design to a user-oriented, personalized design. From product function development to product packaging design, every aspect leverages internet-based thinking to establish connections with users, aiming for greater interaction in order to create effective production plans that emphasize user participation and respect for individual user needs. The \"attention economy\" in the consumer internet sector has reached a certain market bottleneck. Luo Zhenyu, the founder of Luoji Siwei, once mentioned an interesting concept called GDT, which stands for total national time. In fact, today’s internet companies, including BAT, are competing primarily for people’s time. The \"value economy\" created by the industrial Internet, which relies on advanced information technologies, is gradually moving from the background to the forefront, and it is developing at a rapid pace thanks to a value scale that is unmatched by the consumer Internet. The industrial Internet imposes more complex requirements in terms of technology, security, and data. The consumer Internet is easier for users to understand, as it is accessible to most people, and it improves the efficiency of overall transactions ； The industrial Internet is different; it exists within the production process, connecting devices, products, and systems with varying levels of digitization and intelligence, with the goal of improving production efficiency. Essentially, the industrial Internet is the key mechanism through which the Internet expands from the consumer sector to the production sector, and from the virtual economy to the real economy. It represents a set of solutions that enable the manufacturing industry to become digital, networked, and intelligent based on public clouds, with industrial Internet platforms serving as the core of these solutions. Industrial Internet platforms build more accurate, real-time, and efficient data collection systems by integrating emerging technologies such as the Internet of Things, big data, and artificial intelligence on top of cloud platforms. This system includes functions for the storage, integration, access analysis, and management of big data, enabling users (i.e., industrial enterprises) to model industrial technologies and experiential knowledge as well as achieve software reuse through this platform. It provides various innovative applications for manufacturing companies in the form of industrial apps, ultimately fostering a manufacturing ecosystem characterized by abundant resources, multi-party participation, mutual benefit, and collaborative development. Compared to the consumer internet, the technical barriers for the industrial internet are much higher. It requires a strong background in industrial control; whether working on software, hardware, or system integration, it is necessary to have an in-depth understanding of specific application scenarios, as well as to know what devices need to be connected in industrial settings and what types of interfaces and protocols are required. Unlike the smart wearable devices and O2O products in the consumer Internet, where it is possible to design low-cost communication methods from scratch, the industrial Internet is a highly fragmented field with a wide variety of field communication protocols such as Profibus, ProfiNet, EtherNet/IP, OPC UA, EtherCAT, etc. The hardware used is complex and operates according to its own set of rules. These protocols must meet the requirements of enterprise users in terms of security, stability, and transmission capabilities. Moreover, the hardware used for industrial connections must fulfill strict standards related to resistance to high temperatures and electromagnetic radiation, as well as the need for stable online connectivity over extended periods of time. From the diversity of connection protocols to the stringent hardware requirements for edge connection devices, it is clear that the technical demands in this field differ from those of consumer Internet applications. Only by mastering and delving deeply into industrial Internet technologies can breakthroughs be achieved in this sector; the industrial Internet inherently requires an industrial mindset. Moreover, the industrial Internet makes use of a great variety of network connection methods, with multiple types of connections coexisting over time; this increases the difficulty and technical challenges associated with the hardware development for connection modules in the industrial IoT. In terms of security performance, the industrial Internet involves trillions of dollars worth of corporate core assets and privacy data. In the field of security, the consumer Internet focuses on protecting personal property and personal information through electronic payment systems. The security framework for the industrial Internet includes six key aspects: device security, network security, control security, application security, data security, and physical safety. Its objectives encompass both the confidentiality of data and the stable and reliable operation of devices. It involves high-value industrial equipment, as well as the core assets and privacy of enterprises worth trillions. At the same time, the industrial Internet also involves issues related to personal safety due to human operation. Whether it is information protection or asset management, the industrial Internet will have higher and stricter security standards. Taking aerial work equipment as an example, in an industry characterized by high risks, more than 50% of construction accidents in China occur due to falls from heights. As work at heights becomes more frequent, and with an increasing emphasis on safety in such activities, how can we ensure proper functionality of the equipment used for working at heights? Xingbang Heavy Industry, a company specialized in the production of equipment for working at heights, believes that, during such operations, traditional methods of information exchange, such as ERP systems or communication via phone or email, make it difficult to obtain timely and accurate feedback. For equipment like aerial work platforms, which require extremely high levels of safety, this is a very dangerous situation. Yet this problem is widespread in the industry and has yet to be resolved. In the industrial sector, as is generally the case with work at heights, industries such as boiler manufacturing, power generation, textiles, and machine tool manufacturing are considered “high-risk” industries; even the slightest mistake can lead to consequences and losses that are unimaginable. Not to mention the economic losses, in most cases it involves the actual operators. Therefore, the industrial Internet imposes extremely strict requirements on product safety. In the context of big data, industrial big data is massive in volume and grows at a rapid pace. Big data technologies have been in use in the Internet sector for a long time, whether in consumer Internet or industrial Internet, but there are fundamental differences between the big data in these two fields. The essence of the industrial Internet lies in the network connectivity among machines, raw materials, control systems, information systems, products, and people. By enabling comprehensive and in-depth perception of industrial data, real-time transmission and exchange of such data, rapid computation and processing, as well as advanced modeling and analysis, it facilitates changes in production organization methods such as intelligent control and operational optimization. The volume of big data generated is extremely large, and the amount of growth as well as the speed of growth are also enormous. Currently, large manufacturing enterprises in China generate data amounts on the order of TB, creating core business data with high value density. The volume of machine data can reach the PB level (1PB=1024TB); it constitutes the main source of \"big\" data, yet its value density is relatively low. Taking fan equipment as an example, in accordance with the IEC61400-25 standard, the data sampling frequency for the fault conditions of fans operating continuously is 50 Hz; each fan generates 225 K bytes of sensor data per second. Assuming 20,000 fans, the writing rate when all data is collected would be 4.5 GB per second. With the development of intelligent manufacturing and industrial Internet technologies, there is an increasing trend toward reduced human involvement, even complete automation, in the product manufacturing phase. Meanwhile, monitoring of the operational status of products during the maintenance phase is becoming more sophisticated. In the future, the proportion of data generated by humans will decrease, while the amount of data produced by machines will increase exponentially. On the other hand, big data in the industrial sector requires not only fast data collection but also fast processing speeds. An increasing amount of machine data from sources other than industrial information systems is being incorporated into big data systems, particularly the massive volume of time-series data generated by sensors; the speed at which this data is written can reach millions to tens of millions of data points per second. The speed of data processing is reflected in the real-time nature of automatic device control, as well as in the real-time nature of business decisions within enterprises – that is, the rapid response enabled by vertical, horizontal, and end-to-end information integration, as emphasized by Industry 4.0. Generally speaking, industrial data differs from internet data in five main aspects: it is obtained from multiple sources, the data is scattered, and a large proportion of it is unstructured ； Data contains complex information with strong correlations ； Continuous collection, with distinct dynamic spatio-temporal characteristics ； High real-time requirements for collection, storage, and processing ； It is closely related to specific industrial fields. Furthermore, the growing volume of big data in the industrial Internet puts pressure on traditional computing models. The more efficient use of hardware resources by cloud computing provides essential support for processing large amounts of data, and its mature development serves as a necessary foundation for dealing with the ever-increasing amount of industrial data that requires computation and storage. As technology improves, cloud computing costs continue to decline, which is beneficial for the promotion of the industrial Internet. The application scenarios of the industrial Internet are highly fragmented. Most mobile apps come in both personal and enterprise versions: there are enterprise versions of Didi, WeChat, recruitment services, collaborative work tools, as well as enterprise QQ, among others. Generally speaking, to register an enterprise version application, as long as the company details and information are completed, it can be put into operation. Thanks to the development of Internet technology, enterprise applications can be easily standardized, allowing enterprise users to get started with just a few simple steps. The industrial Internet is different; its high degree of fragmentation prevents it from being that flexible. As mentioned in the previous text, enterprises vary widely in terms of their digital and intelligent capabilities, and the devices, products, and systems they use are equipped with a vast array of different interfaces ； The technologies used are complex, including emerging technologies such as the Internet of Things, sensor technology, cloud technology, and big data technology, which have gradually matured. These technologies must be combined with existing automation technologies and industrial software in order to create an industrial Internet solution for a company. Simply put, the industrial Internet today is like a smartphone that can be broken down into various component parts, which can then be further divided into different processes. This has led to the fragmentation of the industrial Internet industry and the modularization of production. On the other hand, industrial Internet clients come in a wide variety, with complex requirements; many specific needs are addressed at the SaaS layer, while expertise in specialized fields is reflected in the delivery of end-products. This requires industrial internet platforms to possess the capability to integrate communication technologies, IT technologies, data technologies, and industrial technologies. For this reason, the CTOs of industrial Internet companies generally have experience in both the industrial and computer fields, whereas the CTOs of consumer Internet companies usually have a background solely in computing; expertise in that field is sufficient for them to fulfill their role. Compared to the consumer internet, the industrial internet requires more experienced technical professionals. It demands a broader range of knowledge and higher levels of skill from R&D personnel; not only do they need expertise in areas such as industry and computing, but they also need around 10 years of technical experience in industrial enterprises. In addition, they must possess the ability to conduct data modeling, enabling them to analyze the industrial big data generated by machinery and business systems, and to transform this data into actionable services that can be used to optimize equipment and business operations. In short, industrial Internet technology engineers transform the operational principles and knowledge associated with the entire manufacturing process – including industrial R&D and design, production, and management – into explicit forms, models, and code, and even enable value creation, something that is beyond the reach of technology engineers in the conventional consumer Internet sector. Industrial Internet companies compete in the market, and their attraction to as well as demand for high-tech talent also influence the direction of their development in the future. Looking at the top industrial Internet companies around the world, their CTOs and the teams they lead play a role in shaping the direction of the companies as well as the products and services they offer. For example, Vic Abate, GE’s Chief Technology Officer, used to be the president and CEO of GE’s Power Generation division and has expertise in wind energy and thermal power technologies; Siemens’ CTO, Bollerin, has been with the company for 24 years since 1994, and is skilled in areas such as research and development and strategy ； Werner Vogels, a top expert in the field of cloud computing, as well as Amazon’s former CTO and vice president, was once a research scientist in Cornell University’s computer science department, where he focused on developing highly reliable and scalable enterprise systems. Today, some companies in China’s industrial Internet sector are facing an increasing demand for talent, and with the goal of becoming world-class industrial platforms, they place particular emphasis on recruiting technical experts and their teams. For example, Zhao Feng, Haier’s CTO, spent the previous 10 years at Microsoft Research Asia before serving as its executive deputy director ； TreeRoot Interconnection has brought in Liu Zhen, former head of Microsoft’s Asia Engineering Group and current CTO at Logitech, to join its team. With over 20 years of experience in the fields of ICT, the Internet, cloud computing, and artificial intelligence, Liu Zhen’s ability to integrate communication technologies, IT technologies, data technologies, and industrial technologies helps to further enhance the company’s capabilities in industrial Internet platforms. Currently, the innovative development of the Internet and the new industrial revolution are at a historical intersection. The world is seizing the opportunities presented by the new round of industrial revolution, accelerating efforts to develop the industrial Internet around key standards, technologies, and platforms in order to create a new digital-driven industrial ecosystem; competition on the international stage for the development of the industrial Internet is becoming increasingly fierce. To stand out in this competition, a strong technical leader is essential; the CTO and his technical team will determine how far the industrial Internet company can go. But just as before the establishment of TreeRoot Interconnection, Sany Heavy Industry had been active in this industry for decades; only by introducing standardization to it was it able to achieve remarkable success in the industrial Internet sector. “By staying focused on solitude and delivering solid performance in each niche sector of the industrial Internet, I believe RootIo has a great chance of success. ”Liu Zhen, CTO of TreeRoot IoT, said that he is currently working on establishing the company’s artificial intelligence laboratory, which will help further drive the development of TreeRoot IoT’s business and enable more intelligent services to be implemented in various industries. Therefore, we can predict that in this wave of industrial internet development in China, the core competition for dominance will be the competition for talent. Only a R&D team led by a CTO with an international perspective and in-depth expertise in big data and artificial intelligence algorithms can contribute a world-class platform to China’s industrial internet industry. We expect that, in this wave of the industrial Internet trend, all platform-based companies will solidly strengthen their product capabilities. Rather than focusing solely on marketing efforts, they should leverage their strengths in product technology, integrating their understanding of the industrial sector with advanced technical solutions – only in this way can they truly bring tangible value to China’s industry and contribute to China’s goal of becoming a global industrial power at an early date. Source: Digital display instruments http://yunrun.com.cn/product/