Intelligent Operation for Gas Gate Stations through AI & Edge Computing with EMQX

Background

The intelligent dispatch system of the natural gas gate station involves utilizing real-time data collection(such as gas supply volume, gas pressure, temperature, etc.), combining information like weather and user demand, and using AI algorithms and models for prediction and optimization.

Compared to traditional experiential manual operations, the gate station's intelligent dispatch system can better manage and optimize operations, improving the accuracy and efficiency of gas supply. This, in turn, reduces operational costs and risks, holding significant importance for both gas supply companies and users.

Challenges of Building an Intelligent Dispatch System for Gas Gate Stations

Building an intelligent dispatch system for gas gate stations presents several challenges that must be addressed to ensure its effectiveness and reliability.

• Difficulty in Data Aggregation: Gate station equipment generates diverse industrial data with heterogeneous communication protocols and message formats. Traditional industrial data collection solutions struggle to support the real-time and historical data processing needs of AI algorithms in a unified format.
• High Precision Data Requirements: The core of AI relies on algorithms. Achieving high-value, high-frequency, and high-precision data flow for AI algorithms in the complex structure of industrial data is challenging.
• Management of Intelligent Edge Computing: Intelligent edge computing at gate stations involves more devices and nodes than traditional centralized computing. Efficient management and monitoring of these devices are vital for ensuring reliability and performance.

EMQX MQTT Platform for Intelligent Gas Dispatching and Management

EMQ offers a powerful solution that utilizes edge computing and cloud technology for intelligent management of gas gate stations.

• At the edge: The edge industrial gateway, NeuronEX, facilitates the integration of various industrial devices. It can convert dozens of industrial protocols into MQTT for real-time perception and stable transmission of various data in weak network environments. NeuronEX also supports streaming data processing and storage at the edge, as well as AI algorithm integration and optimization, catering to specific business scenarios such as device energy optimization, edge intelligent dispatch, and predictive maintenance.
• In the cloud: The EMQX enterprise MQTT platform, deployed in the cloud or data center, provides high availability, high concurrency, low latency, and secure data transmission, analysis, and integration capabilities for cloud-based data systems and business applications. EMQX writes real-time station data into a real-time database at a performance rate of over 10,000 TPS, reducing the processing pressure on applications and algorithm modules, and enhancing the real-time accuracy of AI training.

What You Can Achieve with EMQX

Scalable, Open, and Agile for 40% Efficiency Boost

EMQX delivers standardized capability with open interfaces, horizontal scalability, and hot-swappable configurable functional modules. It supports flexible integration of new devices based on the existing architecture, easily responding to business demands at the edge and the cloud, boosting business platform development efficiency by over 40%.

Manpower and Operational Costs Reduced by Over 60%

The EMQX MQTT platform enables users to achieve centralized management. Users can perform unified operation and maintenance configuration of edge intelligent computing for each station in the cloud. This contrasts with the traditional operational approach of on-site configuration modification and fault diagnosis for edge-side products, leading to a reduction of over 60% in manpower and operational costs.