[Image: image_1.jpeg]Copyright©2025 Yonyou Group All rights reserved.Without the written permission of Yonyou Group, no part or whole of the content of this release note may be copied, reproduced, translated, or reduced for any purpose. The content of this release note may change without notice, please be aware. Please note: The content of this release note does not represent any commitment made by Yonyou Network.Special StatementDear readers, please note that the release notes for this version have been optimized, and there is no longer a distinction between the full version and the incremental version. For easier reading, we have highlighted the new features in bold blue font in the full version. We kindly ask readers to pay special attention to this change while reviewing.Table of ContentsChapter 1 Product Overview 41.1 Product Overview 41.2 Product Architecture 61.3 Product Objectives 7Chapter 2 Product Scope 8Chapter 3 Product Features 83.1 AIoT 83.1.1 IoT Middleware 93.1.2 Enterprise Backend 133.1.3 Twin Modeling 173.1.4 IoT Magic Cube 23Chapter 4 Special Instructions 264.1 Globalization 264.2 Ecology 26Product OverviewProduct OverviewWe believe that the core value of the IoT platform lies in connection, empowerment, and innovation. Connecting the physical world with the business world to achieve the integration of real-time data and business data; empowering data analysis and app development to provide decision support information; innovating business processes and business models. Our use of big data analysis, artificial intelligence, cloud computing, and edge computing technologies effectively supports the connection, empowerment, and innovation in the IoT world:Yonyou AIoT Smart IoT Platform is the foundational capability platform released by Yonyou in the IoT domain. It serves as the device data entry point for Yonyou's next-generation business innovation platform, YonBIP, and is the foundational base for the industrial internet platform.AIoT, which stands for AI + IoT, is the combination of artificial intelligence (AI) technology and the infrastructure of the Internet of Things (IoT). Unlike IoT, which simply collects data, AIoT can utilize AI technologies such as ML/DL to analyze the massive amounts of data collected by IoT with little or no human intervention, helping humans formulate strategies, improve human-machine interaction in IoT, and enhance data management and analysis capabilities, achieving more efficient IoT operations. Yonyou's AIoT products combine the technological advantages of AI and IoT with the advantages of the YonBIP platform aimed at enterprise services, and are widely applied in various industrial domains, achieving upgrades in intelligence and automation.Design Optimization: The application of artificial intelligence in smart innovation primarily assists in product structure design and emulation analysis. During the structure design process, enterprises generate a large number of structural components and model libraries. In the optimization management of the model library, utilizing AI technology can significantly enhance the efficiency of building and applying the enterprise's knowledge base.In the process of multi-physical field emulation, AI technology can better optimize the simulation field, accelerate data analysis speed, and optimize manual modeling. Additionally, material emulation and topology optimization based on 3D printing technology will also benefit from AI technology.Optimize Production Scheduling: In modern digital factories, access digital twin technology to simulate and analyze the factory's production workflow. AIoT can generate optimal production schedules, achieving efficient scheduling under multiple boundaries and constraints. This reduces material and capacity waste, quickly responds to factory production demands, and improves production efficiency.Optimize Supply Chain: An intelligent system covering the upstream and downstream of the supply chain can monitor the full life cycle of enterprise products, accessing AIoT smart accounting data. Based on raw material quotations, component quotations, product quotations, and market trends, coordinate production, supply, and sales to formulate reasonable strategies, reduce inventory, lower costs, and optimize the entire supply chain workflow.Predictive Maintenance: Through AIoT data collection, based on digital twin models, simulate and analyze the equipment in various stages of industrial workflows. Predict the operating conditions of the equipment over a period of time, and implement precise maintenance based on the operating conditions to minimize downtime risks and reduce downtime.Product ArchitectureAIoT Product Application Architecture DiagramAs shown in the above image, the Yonyou IoT platform can be divided into four layers:1) Edge Layer - Edge: Provides a series of services such as protocol conversion, data persistence, and data analysis at the edge, enabling easy data transmission to the platform layer without considering the connection method, while also supporting the execution of critical business processes at the edge.2) Platform Layer: Provides the capability to access original data, the ability to process massive amounts of data, integration capabilities with business systems, and offers an end-to-end IoT application development toolset (access and control of IoT data, management of edge, visual configuration, notification and alarm, etc.);3) Data Fusion Layer: By building data modeling capabilities for IT and OT, using low-code technology, streaming computation, and visualization, applications covering five major domains are constructed, including achieving production interconnection, equipment interconnection, public facility interconnection, and personnel interconnection;4) Data Bridge Layer: Provides a unified data publishing capability that supports unified authentication, security, rate limiting, and monitoring. It offers a configurable position-based business scenario, establishes the association between business data and IoT application data, and realizes intelligent business solutions.Through a single platform, multiple factories deploy to achieve automated task collaboration and provide accurate, reliable, and continuous data service for the management side;Product GoalsThe IoT platform is a one-stop comprehensive solution for the entire IoT ecosystem, serving as the foundation for device digitization and the cornerstone of digital transformation for industrial enterprises. Edge computing is responsible for data access and preprocessing, reporting data to the platform, and accepting unified scheduling and operations from the platform; the IoT middle platform is responsible for unified modeling of devices, as well as unified management and operations of the edge side, along with the storage and publication of time-series data; the IoT cube provides visualization and analysis capabilities for IoT data; twin modeling achieves a modeling method based on the integration of the physical world and the IT world, enabling unified modeling of physical models.Edge Data Collection: Collecting device data close to the equipment, supporting common industrial protocols and open access methods;Unified management and operation of IoT devices: Through the data middle platform, build a ubiquitous, quantifiable, and visual decision analysis system to assist enterprises in establishing decision views as needed for different levels and decision-makers, effectively addressing the shortcoming of "Eastern management being stronger in qualitative aspects."Device Data Visualization: IoT Cube is a data visualization development tool that uses a canvas-based layout and drag-and-drop construction. The development results are WYSIWYG (What You See Is What You Get), suitable for configuration monitoring dashboards, production progress dashboards, remote device monitoring, and other business scenarios.Processing of equipment data and integration of IT data: Twin modeling is a core aspect of AIoT digital twin technology, serving as the data integration platform and data analysis platform for AIoT. The digital twin is dynamic, interacting in real-time with data from the physical entity layer, achieving a fusion of virtual and physical. In twin modeling, personnel information, material information, and task data from the ERP system and MES system can be integrated with the structure, status, behavior, and functionality of the equipment, thereby enhancing the accuracy, relevance, and value of data processing, and realizing business intelligence and automation. It reveals deeper insights, drives innovation, and creates new value.Product RangeThe scope and form of product release are as follows:Domain CloudDomainAppExclusive CloudPrivate CloudOn-PremisesiuapAIoTIoT Middleware✔✔✔iuapAIoTEnterprise Backend✔✔✔iuapAIoTTwin Modeling✔✔✔iuapAIoTIoT Magic Cube✔✔✔Product FeaturesAIoTYonyou's data middle platform integrates data aggregation and fusion, data processing, data governance, and data visualization into one. Through multi-source heterogeneous big data synchronization, data modeling, data standards, data assets, data services, data display, and monitoring functions and technical methods, it achieves data service visibility. By providing a user-friendly data service development environment and advanced data analysis capabilities, it lowers the technical threshold and reduces the cost of data processing for enterprises, facilitating a data-driven business pathway, realizing business value across departments, and ultimately achieving the monetization of data value, providing strong momentum for the digital transformation of enterprises.The data middle platform is dedicated to empowering enterprises to realize value from data, with the main value reflected in:Multi-business aggregation, breaking down enterprise data silos;Strong development capabilities, standardized and efficient data value extraction;Refined Data Governance, standardizing and controlling data with high quality;Special asset management to achieve quantifiable value of data elements.Stunning data presentation, perfectly insighting the overall business landscape;Lightweight agile self-service, analyze data with WYSIWYG (What You See Is What You Get).IoT MiddlewareIn the current version, a portion of the common capabilities has been separated out to facilitate different roles in quickly finding the required functions during use. The Data Middle Platform Foundation mainly includes the Configuration Center, Approval Center, and Operation and Maintenance Center.Physical ModelThe object model is a collection of devices, usually referring to a group of devices with the same functionality. The IoT platform issues a globally unique ProductKey for each device model.Function Description:The physical model is represented as an abstract model of the device, mainly used to describe the capabilities and properties of a specific device. After defining the device model, it can be selected when creating a device.Create Object ModelCreating a physical model can be done in two ways: manual creation and template import.Functions Included in the Physical ModelBasic Information;Property Configuration;Event Configuration;Control Configuration;Event Configuration.Drive the MarketThe current market for drivers includes 12 commonly used driver agreements for the AIoT platform, with detailed access documents for each driver to facilitate quick access for users.GatewayA device with gateway functionality can connect multiple devices through channels, typically integrating the devices of a factory or region into the same gateway. The configuration of collection devices under the same...
