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Difficulties and cost of data access

The difficulties and cost of data access are two of the core pain points that restrict the application of industrial Internet platforms. Industrial equipment types are complicated, equipment manufacturers are numerous, a large number of private protocol create access difficulties, older equipment does not have digital capabilities, and the full amount of data collection is difficult. In the absence of unified management, storage, application, and data compliance, it is difficult to realize data value mining.

Edge intelligence and cloud-side collaboration capability requirements

Traditional SCADA and DCS systems cannot meet the new industrial Internet requirements for data transmission, storage, edge processing, and real-time display and retransmission. To meet industrial real-time requirements and reduce network and IT resource consumption, data analysis at the edge is becoming a must for industrial Internet platforms.

Data Value Underutilized

A large amount of historical data is collected, but no unified management, storage, or application is realized. The collected data has poor compliance and is difficult to generate effective value. Intelligent applications are built independently and cannot share and interoperate with each other effectively.


In the EMQ Industrial Internet solution, Neuron, the edge industrial protocol gateway software, can support Modbus, OPC-UA, IEC61850, IEC104, and other complete industrial protocols to realize efficient access to data of various heterogeneous industrial equipment. The data collected in real-time is captured, filtered, complemented, and time-windowed calculated at the edge using eKuiper, a lightweight edge streaming processing engine, to provide a high-quality data source for edge AI inference services.

The solution supports both local deployment and multi-location, multi-node distributed deployment, providing flexible and diverse edge cloud data channels. The edge can achieve high real-time data response through lightweight deployment; SQL-based edge streaming data processing effectively reduces cloud-side transmission costs, and the overall flexibility and scalability can significantly improve the integration of enterprise personalized edge-side.

EMQ empowers industrial data, allowing data to be analyzed with data from other business systems (such as ERP, CRM, etc). EMQ also provides various data interfaces and various data persistence and message queue interfacing capabilities, with standard rich RESTful APIs for external application integration to obtain more valuable analysis results.



  • Based on EMQ IoT data infrastructure software, the industrial Internet platform provides one-stop access to IoT protocols, industrial protocols, and private protocols to realize the unified collection of massive and high-frequency industrial data. It also provides a good data foundation for big data analysis and artificial intelligence applications by connecting, moving, storing, processing and analyzing data in real-time at the cloud side. This helps enterprises quickly build upper-layer applications.
  • The original way to build applications was to build applications around data. This made enterprises become data-driven to help drive future-oriented IoT key business applications.