Core Viewpoint - The book aims to provide a comprehensive and practical guide on industrial data acquisition technology, highlighting its increasing importance in industrial production, management, and decision-making processes as China's economy rapidly develops [2][3]. Summary by Sections Chapter 1: Overview of Industrial Internet - Introduces the background and development of industrial internet technology, its concept, architecture, and significance [3]. - Discusses industrial data acquisition technology, including its characteristics and solutions [3]. - Covers the role and structure of industrial gateways and provides an overview of industrial internet experimental platforms [3]. Chapter 2: Industrial PLC Data Acquisition - Details the principles, hardware architecture, programming methods, and practical applications of PLC data acquisition technology [4]. - Explains the concept, structure, and working principles of PLC, along with its widespread applications in industrial automation [4]. Chapter 3: Industrial Ethernet Data Acquisition - Discusses the concept, protocols, and application scenarios of industrial Ethernet data acquisition technology [5]. - Focuses on the working principles of two mainstream industrial Ethernet protocols: PROFINET and EtherCAT, including device connections and communication protocols [5]. Chapter 4: Embedded Data Acquisition - Introduces embedded technology theories and its applications in industrial data acquisition [6]. - Analyzes ARM processor architecture and provides detailed explanations of STM32 microcontroller usage [6]. Chapter 5: ZigBee-based Wireless Data Acquisition - Provides a comprehensive overview of ZigBee technology and its applications in wireless sensor networks [7]. - Discusses the design of wireless sensor nodes based on CC2530 microcontroller and showcases practical applications of ZigBee in data acquisition [7]. Book Features - Comprehensive content covering various industrial data acquisition technologies, including concepts, principles, methods, and practical cases [8]. - Strong practicality by closely linking theoretical knowledge with real-world industrial applications [8]. - Rich in practical application cases to enhance understanding of industrial data acquisition technology [8]. Supplementary Resources - The book includes source code, teaching materials, syllabi, progress tables, experimental manuals, and question banks to facilitate teaching and learning [9]. Target Audience - The book serves as a textbook for higher education institutions in fields like IoT and industrial internet, and is also suitable for professionals in automation, smart manufacturing, and IoT, as well as enthusiasts interested in industrial data acquisition technology [10].

Group 1 - The conference in Shanghai focuses on "AI serving the real economy through digital technology integration," with over 1200 representatives from various sectors including communication, industry, healthcare, and consumer goods [1] - Companies are exploring how to utilize AI to optimize supply chain decisions and integrate generative AI into product design and customer service processes [1] - The challenge of "affordability" and "usability" of AI models, especially those with hundreds of billions of parameters, is hindering the realization of AI benefits [1] Group 2 - The integration of AI models into production lines is being showcased, highlighting the ability of industrial robots from different manufacturers to collaborate through a smart platform [6] - The CTO of a telecommunications company stated that switching packaging on a regular production line takes two to three days, while using robots can reduce this time to just half an hour with proper training [8] - The flexibility of production lines driven by embodied intelligence requires enhanced infrastructure capabilities, particularly with the integration of 5G-A networks and AI [10] Group 3 - The construction of a universal and rapid development platform, referred to as the MaaS platform, provides low-code and no-code tools for developing large AI models, supporting over 40 industry-specific models and 100 application scenarios [10] - This platform aims to help companies reduce costs, improve quality, and increase efficiency [10]

Group 1 - The core viewpoint emphasizes that information interconnectivity is a key engine for the quality upgrade of supply chains, with China having built the world's largest and technologically advanced information communication network, achieving full coverage of 41 industrial categories through the industrial internet [1] - A consumer in Europe can input specific requirements via mobile, and the data is transmitted through a 5G network to Chinese manufacturing enterprises' industrial internet platforms with an end-to-end latency of less than 20 milliseconds, significantly enhancing manufacturing efficiency [3] - The improvement in manufacturing efficiency is supported by digital infrastructure centered around computing power, with the "East Data West Computing" project initiated in 2022, aiming to establish eight major hub nodes and ten national data center clusters by the first quarter of 2025, achieving a total computing power of 215.5 billion billion floating-point operations per second [5] Group 2 - China has established 4.486 million 5G base stations and over 100 million connected industrial devices, enabling diverse applications through adaptable computing power, with more than 30,000 basic intelligent factories and over 1,200 advanced intelligent factories operational, covering over 80% of major manufacturing sectors [7] - The integration of information chains accelerates efficient communication between upstream and downstream sectors, facilitating quality upgrades in manufacturing [7]

Group 1 - The event focused on the integration of education and industry, highlighting the launch of a new school-enterprise cooperation plan and upgraded training direction for the MBA/EMBA programs at Shanghai University of Finance and Economics [1][2] - The "Business Chain Symbiosis" initiative aims to enhance collaboration between academia and industry, addressing the challenges of the evolving business ecosystem and fostering a new educational paradigm [2] - The new training direction includes seven modules designed to promote industry-education integration, such as expert-led forums, industry park visits, and practical projects that solve real business problems [2] Group 2 - A cooperation awarding ceremony took place, with nine organizations recognized as "MBA Talent Training Practice Bases," covering cutting-edge fields like artificial intelligence, biomedicine, and industrial internet [3] - This recognition signifies a significant step forward for the "Business Chain Symbiosis" plan, expanding the network of collaboration between schools and enterprises [3]

Group 1 - The core viewpoint of the article highlights how the integration of industrial internet and AI can enhance brand value, exemplified by the Kaos COSMOPlat platform, which has achieved a brand value of 116.335 billion yuan, an increase of 13.558 billion yuan from the previous year [1] - The World Brand Laboratory's report emphasizes that AI is now a central driving force in global brand strategy and digital supply chain management, facilitating a shift from product-centric to consumer-centric approaches [1] - The Kaos COSMOPlat platform has been recognized as a leading case in the development of industrial AI models, supporting over 45 high-value scenarios across nine industries, including home appliances and energy [3] Group 2 - The Kaos COSMOPlat platform has collaborated with Yanchang Petroleum to create an energy and chemical model, resulting in the development of 38 intelligent agents that enhance efficiency by an average of 20% in oil extraction and refining processes [3] - The platform's smart chemical park solutions have been implemented in over 30 chemical parks across more than 10 provinces, serving over 400 chemical enterprises [4] - In the Anhui Changfeng County industrial park, the energy utilization efficiency has improved by 20% and carbon emissions have been reduced by 15%, equivalent to the carbon absorption capacity of an additional 2,000 acres of forest [4]

Group 1 - The completion of the "10,000-Channel Factory" demonstration project by China Aluminum Guangxi Company marks a significant upgrade in the industrial internet infrastructure in Pingguo, Guangxi, enabling digital and intelligent transformation for industrial enterprises [1] - The project utilizes a "full optical base + industrial PON" architecture, achieving end-to-end 10G network coverage and integrating cutting-edge technologies such as industrial OTN and optical bus [1] - The 10G optical network features a single wavelength bandwidth of 50Gbps and deterministic network latency, catering to demanding industrial internet applications like 8K visual inspection and cloud-based robot control [1] Group 2 - The factory's production processes have been transformed, enabling real-time data transmission from raw material storage to finished product delivery, significantly enhancing production efficiency and accuracy [2] - Remote equipment control experiences near-zero latency, allowing for synchronized command issuance and device response, which supports rapid data transmission and in-depth analysis for informed decision-making [2] - The project supports intelligent application platforms such as industrial AOI systems, digital twin systems for production processes, and intelligent safety monitoring platforms, contributing to high-quality industrial development [1][2]

Core Insights - The core industry scale of industrial internet in China exceeds 1.5 trillion yuan, driving economic growth of nearly 3.5 trillion yuan, with artificial intelligence becoming a key variable in the development of industrial internet [1] Group 1: Industrial Internet Development - The industrial internet has expanded to cover 49 categories of the national economy, achieving full coverage of 41 industrial categories, with over 6.5 trillion identification registrations and connections to over 100 million industrial devices [2] - A multi-level platform system has been established, consisting of 49 cross-industry platforms and over 200 specialized platforms, supporting a wide range of application needs from general to industry-specific [3] Group 2: AI Integration in Industrial Applications - AI technology is being deeply applied in industrial scenarios, with companies like 蓝卓数字科技 leveraging their "supOS" factory operating system to facilitate digital transformation across over 8,000 factories in various industries [4] - 卡奥斯 has upgraded its "twin manufacturing integrated platform," which merges virtual production with physical manufacturing, optimizing the entire manufacturing lifecycle [5] - AI applications in engineering machinery and supply chain management have demonstrated significant efficiency improvements, such as a 60% increase in energy replenishment efficiency and a 30% improvement in inventory turnover [6][7] Group 3: AI and Industrial Internet Synergy - The integration of AI and industrial internet has led to the emergence of numerous application models, with a focus on both small models for specific tasks and large models for comprehensive industrial intelligence [8] - The development trend indicates a collaborative fusion of large and small models, where large models handle task planning and coordination, while small models execute specific tasks effectively [8]

Group 1 - The Jiangxi Provincial Development Zone Unified Digital Management Service Industrial Internet Platform aims to integrate various industrial management departments, industrial parks, and enterprises through big data and cloud architecture, enhancing government oversight and macro-control effectiveness [2][3]. - The platform has been implemented in over 100 provincial-level development zones, covering 59,000 industrial enterprises and accessing 4 billion industrial information data, successfully responding to service demands over 1.854 million times [2][3]. - The platform serves multiple industries including non-ferrous metals, electronic information, equipment manufacturing, petrochemicals, building materials, textiles, food, automotive, biomedicine, semiconductor lighting, and energy conservation and environmental protection [3]. Group 2 - The platform offers a comprehensive digital transformation system for enterprises, utilizing SaaS deployment to provide solutions for common challenges across various business functions, including sales, warehousing, design, production, and finance [4]. - The Just-in-Time Delivery System enhances order management by automating processes from order placement to delivery, improving order completion rates and providing data-driven insights for decision-making [6]. - The PBA Project Management Platform streamlines project lifecycle management, improving budget efficiency and reducing labor costs by allowing departments to input data directly into the system [8]. Group 3 - The Smart Warehouse System automates inventory management processes, enhancing accuracy and reducing manual labor by integrating various management functions such as procurement, inventory, and financial management [10]. - The Gaoshu Industrial Internet Platform focuses on digital transformation solutions for industrial enterprises, leveraging IoT, digital twins, big data analysis, and AI to improve production efficiency and reduce costs [13][14]. - The platform has successfully implemented solutions across various industries, receiving high praise for its stability, usability, and value [13].

Core Viewpoint - The Guangdong-Hong Kong-Macao Greater Bay Area Industrial Internet Public Technology Service Platform has been recognized as a key pilot platform, marking its role as a crucial hub for the industrial internet technology transition from research and development to industrial application in China [1][2]. Group 1: Importance of Pilot Platforms - Pilot platforms address the "last mile" challenges in manufacturing, such as equipment interconnectivity, data silos, and high trial costs, acting as an intermediary testing ground for technology validation and industrial application [2]. - The Greater Bay Area Industrial Internet Platform aims to integrate cutting-edge technologies like 5G, big data, and artificial intelligence to create a comprehensive industrial internet technology verification and service platform [2][3]. Group 2: Technical Integration - The platform offers services across six major pilot verification production lines, enhancing trial verification efficiency by 30%, reducing comprehensive trial costs by 50%, and shortening R&D cycles by 50% for small and medium-sized manufacturing enterprises [3]. Group 3: Data Utilization - The platform aggregates eight categories of heterogeneous industry data, improving data collection efficiency by 20% and equipment utilization by 15%, thereby promoting industrial digital transformation and high-quality innovation [5]. Group 4: Ecosystem Collaboration - The platform is co-built by Shenzhen National High-tech Industry Innovation Center and major companies like Huawei and China Unicom, establishing a three-tier collaborative model to support small and medium-sized manufacturing enterprises [8]. Group 5: Lightweight Transformation - The platform introduces a "lightweight digital transformation" approach for small and medium enterprises, providing tailored service packages that have already benefited over 2,000 companies in Shenzhen, with plans to expand services to 5,000 enterprises [9].

Group 1 - The core viewpoint emphasizes the urgent need for enterprises to innovate their operational models in the context of deepening industrial internet, with digital operation management becoming a key driver for digital transformation [1][3] - Digital operation platforms serve as crucial support for enterprises, enabling new dynamics in organizational management, business collaboration, and customer engagement, thus promoting the evolution of management logic and supply chain structure [1][3] Group 2 - The industrial internet provides a technological foundation for data perception, system integration, and process optimization, making it an important basis for implementing digital operation management [3][4] - Digital operation platforms connect production processes with management centers, facilitating a closed-loop operation from data collection to decision execution, enhancing flexibility and controllability in response to market changes and customer demands [3][4] - In practical applications, digital operation management demonstrates a high degree of integration, allowing manufacturing enterprises to monitor key indicators like equipment status and energy consumption in real-time through a unified management interface [3][4] Group 3 - Digital operation platforms not only aggregate information but also support strategic collaboration by creating a unified organizational management framework, breaking down hierarchical barriers, and enabling data interconnectivity across the supply chain [3][4] - The platforms enhance efficient collaboration among business units through task boards, process engines, and performance management modules, leading to a more orderly overall operation [3][4] Group 4 - Enterprises can integrate sensors and control systems with digital operation platforms to establish an industrial-grade data collection system, allowing for more granular control in digital operation management [4] - This deep integration enables intelligent responses to material consumption, quality traceability, and predictive maintenance, enhancing the ability of enterprises to manage risks and changes [4] Group 5 - Building scalable digital operation platforms is essential for enterprise development, utilizing microservices, data middle platforms, and low-code tools to achieve multi-system collaboration and flexible deployment [4] - The modular design allows enterprises to deploy systems as needed at different stages, avoiding redundancy and improving the effectiveness of digital operation management [4] Group 6 - User connectivity is a vital component of digital operation, with platforms capturing user behavior across touchpoints to create user profiles, facilitating personalized services [4] - This user-centric digital operation management model enhances overall customer experience and repurchase rates through customized product recommendations and content delivery [4] Group 7 - In the future, enterprises will continue to deepen their understanding and practice of digital operation management, driven by the industrial internet and digital technologies [4] - The evolution of digital operation platforms will increasingly feature intelligent characteristics, incorporating new technologies like artificial intelligence and edge computing to enhance responsiveness to business changes [4]