AI empowers industrial internet and opens a new chapter in industrial digitization!

April 9, 2023

AI + Industrial Internet↓↓↓

IBI, as a platform dedicated to exploring the industrial internet, is based on industrial e-commerce and supported by internet big data. It is committed to the deep integration of new technologies such as the internet, the Internet of Things (IoT), big data, cloud computing, and artificial intelligence with traditional industries, striving to continuously promote the value mission of reducing costs and increasing efficiency for traditional industries.

According to the Ministry of Industry and Information Technology's plan, industrial e-commerce is an important link in the industrial internet and an effective means to promote the development of the industrial internet platform. The core of the industrial internet is "connection," while the core of industrial e-commerce is "commerce." The industrial internet, through the interconnection of machines or equipment, deposits a large amount of data flow. In contrast, industrial e-commerce, focused on the supply chain, forms closed loops of information flow, commerce flow, logistics, and capital chains, effectively realizing the value-added transition from industrial connectivity to data, supply chain, and cross-sector ecosystems, thus becoming a critical tool for grounding and cultivating the industrial internet.

The core of the company's industrial internet strategy is "platform service, technology-driven, data-supported," constructing a new vertical industrial internet ecosystem through platforms, technology, and data. Over years of development, we have been continually advancing strategic planning starting from industrial e-commerce through platform operations to meet the operational needs of entities in trading, delivery, finance, production, and linking. We use digital tools for transactions, supply chain, and operational management to build a technology-driven system for platform operations. With the advancement of platform operations, technology-driven digital transformation and channel connections are happening across supply chain and operational management, precipitating massive data at the trading end, supply chain end, and production end, forming big data support, thus constructing an industrial chain closed loop with platform, technology, and data systems to achieve efficient operation of the industrial internet. The core value of industrial interconnection is to use data to connect multiple industrial links to ultimately achieve the core purposes of value enhancement and cost reduction, essentially fostering its ecosystem gradually.

Therefore, the application of AI in the industrial internet, along with the gradual deepening of industrial transformation, might present two characteristics in the future "AI+Industrial Internet" application model: First, based on massive data collection as raw material, using machine learning or deep learning algorithms as the core to solve specific diagnosis, prediction, and other issues by establishing artificial intelligence models. Second, oriented by user demand, to achieve full-industry chain coverage, providing decision-making assistance in production control optimization, supply chain optimization, logistics scheduling optimization, and market sale forecasting, etc., for enterprises. (Source: CRI Online)

The enhancement of artificial intelligence on the real economy is reflected in various links. For example, in the aspect of production intelligence in manufacturing, AI can act on multiple areas, including automatic sorting, quality inspection, equipment operation, and production process optimization, bringing significant improvements at every link. The role of "smart connectivity" for the industrial internet has been continuously proven, but for real implementation, both carriers and ecosystems are needed. It requires a core competency in artificial intelligence to perceive users, achieve the datafication of natural user interaction, and realize cloud-connected devices through software and service. From this perspective, an industrial internet platform is just such a carrier and ecosystem.

IBI in AI

We believe AI technology is one of the crucial means to optimize production efficiency and innovate business models. In recent years, the company has conducted extensive research and application in the AI field, especially in areas like intelligent recommendation, sales forecasting, purchase forecasting, and machine vision on e-commerce platforms.

01 In the field of intelligent recommendation

To better meet the needs of users in different industries, we employ deep learning algorithms to provide personalized recommendation services for users based on their historical click records, purchase records, preferences, and tags. This recommendation algorithm, grounded in the accumulation and analysis of user behavior data, can more accurately predict user needs, thereby enhancing user satisfaction and purchase conversion rate. Similarly, utilizing recommendation algorithms, we can apply them in more fields, such as during the production process in factories, by collecting past feeding records, procurement records, and operation records to provide material ratio recommendations for production staff or operation recommendations for DCS personnel, such as at what time to add which materials, how much to add, temperature control, and how long the chemical reaction should last; also in the transportation of bulk logistics, predicting the best routes and estimated freight charges.

02 In the dimensions of sales forecasting and purchase forecasting

The company has a vast array of industrial information data, production capacity distribution data, transaction data, customer data, production data, and logistics data, which provide a multi-dimensional analysis advantage for our model training. We can predict the market demand and supply situation for the next 1-3 months, predicting platform user transactions based on historical transaction data. Accurate sales and purchase forecasts can help the platform better grasp market trends and supply chain changes, thereby optimizing product combinations and supply chain management, allowing a better grasp of market demand and supply chain changes to make more accurate predictions and decisions, providing more precise and efficient services to customers.

03 The safe identification of digital cloud factories/cloud warehouses

In 2021, the company implemented a "Three-year Plan for 100 Cloud Factories" primarily to provide more supply chain services and digital technology services to the factory end. Among digital technologies, we applied machine vision technology, using cameras and sensors to monitor production processes on the production line, analyze personnel behavior, detect abnormal changes in warehouse positions, fire alarms, etc., significantly improving the precision and efficiency of safety monitoring and control in factory safety management, contributing to smarter and more efficient production management and safeguarding workers' safety and production stability. For instance, there are usually dozens to hundreds of cameras in a factory, with densely packed monitoring screens in the control room, and personnel is also arranged to watch them, but such manual monitoring is very inefficient. Through deploying corresponding video boxes at the edge, we assist factories in monitoring by observing personnel movement, abnormal temperature, instrument readings, potential fires, smoking, and the trajectory of vehicles and forklifts, providing higher quality AI services to factories at a low cost.

04 Industrial Metaverse - Meta Enterprise

The company has a project called Meta Enterprise in the industrial metaverse. Meta Enterprise can provide a large amount of simulation video data for the development of machine vision technology. In traditional machine vision technology, obtaining a large amount of training data is a challenging and time-consuming process. However, in the metaverse, a vast amount of simulated data can be generated through game engines and simulation environments, which can be used to train various machine vision models such as object detection, image segmentation, and pose estimation. Due to the precise control over various parameters in the simulation environment, such as lighting, material, and environment, the generated data quality is superior, enhancing the accuracy of machine vision models.

Additionally, through game engines and simulation environments in the metaverse, various complex scenes and dynamic effects, such as traffic flow and crowd density, can be generated. This data can be used to train intelligent monitoring, safety detection, and other models, thereby enhancing safety management and early warning capabilities.

05 Integration with ChatGPT

In terms of ChatGPT, as an important new artificial intelligence technology, its algorithms open up novel development ideas in industrial digitization and economic digitization. Currently, the company has fully integrated ChatGPT internally, allowing all employees to use this function on the internal management platform. Through using ChatGPT, R&D personnel can write basic codes and design some plans, accelerating the development process for related systems and platforms. For instance, by conversing with ChatGPT, one can generate system table structures, write Python code for web crawlers, or automate code and UI tests. During use, our product and technical personnel can use it to obtain more comprehensive designs and codes, focusing more effort on technological innovation and service. Additionally, the video team can use ChatGPT to generate some video scripts and live broadcast scripts, improving shooting efficiency; sales and customer service personnel can also use it to organize and refine reply content.
Meanwhile, we are actively interfacing with Baidu's Ernie and Alibaba Cloud's Tongyi Qianwen, with our R&D department also building an enterprise AI application based on these models and services to offer to many platform upstream and downstream customers.

Future Goals↓↓↓

Although AI has penetrated and its maturity is constantly improving in industrial design, production, management, marketing, and sales in recent years, it is still in the early stages of development overall. AI's application proportion at the industry level remains low, and implementation costs are still high. For example, constructing a model requires an investment of several million yuan, which is essentially due to the shortage of AI personnel in the country and market enthusiasm causing the situation.Therefore, the company hopes, through our platform's training and effort over time, to lower the threshold for AI use across the industry, enabling AI to enter every aspect of traditional industries, improving efficiency, and creating more value for real enterprises.

We believe the industrial internet is like a container, capable of containing everything. AI, blockchain, cloud computing, big data, GPT, and other modern technologies can find corresponding application scenarios in the industrial internet, and can be grounded and practiced. As one of the promoters in the field of industrial internet, we will fully embrace the upgrades and transformation brought by AI and other technologies on industries and supply chains in the process of industrial digitization, actively promoting the integration of new technology with traditional industries.

Rizhao City's Deputy Mayor Zhang Jinmei led a delegation to visit IBI, discussing how the industrial digital economy can propel the high-quality development of traditional industries.

Mr. Wang Ting, Director/Senior Vice President of IBI, and his delegation were invited to attend the China-Malaysia Business Event - China Industry Leaders Roundtable Conference.

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