Solving Common Industrial IoT Data Streaming Challenges with MQTT
Struggling with real-time IIoT data flow? Learn how MQTT solves legacy integration, scaling, reliability, and security challenges in manufacturing.
Connect, process, transform, and act on IIoT data in motion, from edge to cloud, for AI-powered decision making with HiveMQ’s reliable, secure, and scalable IoT data streaming platform.
Industrial teams are drowning in machine and sensor data that sits in incompatible formats, blocking real-time decisions and AI outcomes. Real-time Industrial IoT data streaming, built on MQTT, moves data reliably in a standardized structure from edge to cloud. By decoupling devices and applications and using MQTT QoS to ensure delivery, it keeps data timely, trustworthy, and ready for analytics. HiveMQ provides the enterprise-grade platform behind this, offering secure, scalable, and observable data movement so you can connect, process, transform, and act on data in motion for AI-powered decision-making.
Real-time IIoT data streaming helps teams unlock operational efficiency, reduce downtime, enable predictive maintenance, and fuel AI-powered decision-making.
Make real-time production decisions by streaming data that reflects the current state of machines, assets, and operations.
Monitor the condition, performance, and location of distributed assets with live streaming updates.
Feed machine learning (ML) models and analytics tools with structured, real-time data for actionable insights.
Detect anomalies early by analyzing data in motion before critical issues arise.
Access timely performance metrics, such as Overall Equipment Effectiveness (OEE), to fine-tune operations and reduce downtime.
Unify data from operational systems, such as SCADA, MES, and PLCs to enterprise systems to enable holistic decision-making.
Poor data quality costs organizations millions each year, increasing complexity and hindering decisions (Gartner)
Companies successfully operating in real-time environments outperform competitors (MIT)
Organizations utilizing live data insights improve their decision-making speed (Deloitte)
Leading manufacturers, energy providers, logistics organizations, and Industry 4.0 pioneers rely on HiveMQ to stream IIoT data from PLCs, SCADA, and MES systems to cloud platforms like Kafka, securely, at scale, and in real time. With native support for MQTT and Unified Namespace, HiveMQ empowers you to scale a modern IIoT architecture and achieve true IT/OT convergence.
Delivers MQTT the way industrial systems demand it, with support for QoS levels, persistent sessions, LWT, and clustering built in.
Ensures IIoT data is contextualized and compliant so it’s usable in real time and ready for analytics, AI/ML, and enterprise-scale decision-making.
Serves as the real-time data backbone for industrial operations, connecting OT systems with cloud platforms for end-to-end data flow.
Helps industrial teams build Unified Namespace using structured MQTT topic hierarchies, turning siloed machine data into a shared, contextualized source of truth.
Lays the foundation for event-driven architectures and brings DevOps-style agility to OT environments, without sacrificing reliability or control.
HiveMQ is purpose-built for industrial IoT. It enables real-time data movement from edge devices to cloud platforms, securely, reliably, and at scale. With native MQTT support, powerful extensions, and deployment flexibility, HiveMQ forms the foundation for your Unified Namespace, AI/ML pipelines, and digital transformation strategy.
Struggling with real-time IIoT data flow? Learn how MQTT solves legacy integration, scaling, reliability, and security challenges in manufacturing.
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