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Most factories today contain a mix of legacy and new automation equipment from multiple vendors and support software applications ranging in age from a few years to potentially a few decades old. These machines and applications often communicate via hundreds of different machine protocols, generating multiple operational data telemetry streams of operating parameters like pressure, temperature, speed, machine state, and more.
Additional factory data streams from software systems include enterprise resource planning (ERP), machine execution systems (MES), and shift scheduling systems, which manage production workflows, equipment, and workforce coordination. Although data resides in equipment, production software systems, and IT systems, the challenge lies in integrating and making this information accessible to support quick responses to changing conditions while preserving detailed records for long-term historical analysis and process optimization.
MQTT and Unified Name Space (UNS) offer a standardized method for organizing and structuring metadata across the enterprise. By adopting MQTT and UNS, manufacturers establish a unified data framework for extracting, transforming, and loading data for analysis. This approach connects legacy systems with modern applications, facilitating both real-time operational visibility and long-term historical analysis.
AWS IoT SiteWise
Cloud provider AWS announced the general availability of MQTT enabled SiteWise Edge gateways for AWS IoT SiteWise, allowing customers to develop a unified approach to data management. AWS IoT SiteWise is a purpose-built, managed IoT service designed to make it easy to collect, store, and monitor data from industrial equipment to help make data-driven decisions. AWS IoT SiteWise helps gather data from a wide array of industrial equipment and processes, model this data to accurately represent their assets and facilities, process and analyze information in real-time, visualize operations through intuitive built-in tools, and integrate with other AWS services for advanced analytics and machine learning applications.
AWS IoT SiteWise Edge extends AWS IoT SiteWise cloud capabilities to the edge, enabling users to collect, process, organize, and act on industrial equipment data on-premise while delivering that data securely to AWS IoT SiteWise in the cloud. AWS works with partners to integrate consoles and platforms, enabling support for hundreds of protocols and the development of user-defined calculations, alarms, events, and edge processing. Key partnerships include Siemens Industrial Edge, Domatica EasyEdge, Litmus Edge, and Belden CloudRail.
The new MQTT enabled AWS IoT SiteWise Edge gateways enable a publish-and-subscribe data topology (pub-sub) and a hub and spoke integration methodology between software components at the edge. Before this release, AWS internal edge software components and any custom-made edge components required point to point integration using AWS proprietary APIs and software. The pub-sub and hub and spoke concepts use the open source MQTT standard for data transport, simplifying integrations between existing equipment, middleware, and production systems without the need to learn proprietary APIs or have deep programming skills.
Democratizing Data at the Edge and Delivering to the Cloud
MQTT helps establish a logical data hierarchy that mirrors operational structure via a folder-like organization. This creates a unified namespace where production data, machine telemetry data, and system information are organized in a way that reflects how factories operate and report. The AWS IoT SiteWise Edge gateway serves as the hub, collecting data through native OPC UA connectivity, certified partner integrations, and custom edge integrations. As data flows through this MQTT-based architecture, it maintains its contextual relationships while enabling real-time access across operations.
The system combines machine telemetry with metadata from production systems like MES and ERP. As data travels to the cloud through AWS IoT SiteWise Edge, built-in store-and-forward capabilities support near-zero data loss, even during network interruptions. AWS IoT SiteWise enables customers to reflect their edge data structure in the cloud through modeling, where it becomes readily available for advanced analytics.
Building a Unified Name Space: Foundation of Industrial Data Integration
The Unified Name Space (UNS) approach to data management offers a standardized methodology for integrating, organizing, and normalizing operational data. UNS mirrors natural facility organization through a hierarchical topic structure and creates logical pathways that make event-driven data discovery and access straightforward.
Unlike traditional data architectures that focus on storage, UNS functions as a lightweight, dynamic data bus. It maintains current values and relationships without the overhead of historical storage, optimizing both network and system resources. This efficiency is further enhanced by UNS’s technology-agnostic design, which accommodates multiple protocols and transport mechanisms, bridging the gap between legacy systems and modern applications.
AWS IoT SiteWise Edge supports this architecture through two implementation options: establishing a UNS directly with its built-in MQTT broker or leveraging MQTTv5 broker-to-broker bridging to integrate with an existing MQTT infrastructure.
Learn more about Industrial IoT Edge Compute Platforms.