Telemetry

Telemetry is the automated collection, transmission and analysis of data from devices, machines or Industrial Processes over a network connection. Within OT environments, telemetry is used to obtain Real-time insight into operational performance, status information, faults and process values.

Telemetry forms a fundamental part of:

• SCADA
• Industrial Internet of Things
• Industry 4.0
• Industrial AI
• Predictive Maintenance
• Smart manufacturing
• Critical infrastructures

Within modern industrial environments, telemetry delivers continuous data streams from sensors, controllers, robots and other OT components.

📡 What is telemetry?

Telemetry covers the automated measurement and transmission of operational data to a central system for monitoring, analysis or control.

Typical telemetry data:

Telemetry is used for:

• Real-time monitoring
• Historical analysis
• Trend analysis
• Remote diagnostics
• Predictive maintenance
• Process optimisation

🏭 Telemetry within Industrial Automation

Within Industrial Automation, telemetry systems collect data from:

Telemetry supports operational visibility within production processes.

⚙️ Architecture of telemetry systems

A telemetry platform consists of multiple layers.

Typical architecture

Data typically flows from field level to higher OT and IT layers. The platform on which telemetry data is collected is also referred to as a Hoofdpost (master station).

🔄 How telemetry works

A telemetry process usually consists of:

1. Data collection
2. Filtering
3. Normalisation
4. Transmission
5. Storage
6. Analysis
7. Visualisation

Real-time telemetry requires:

• Low Latency
• High Availability
• Reliable communication
• Continuous data streams

📊 Types of telemetry data

Within OT systems, several types of telemetry exist.

Much data is stored in a Historian or Time Series Database.

🌐 Industrial communication protocols

Telemetry uses various OT protocols.

Within modern OT networks, MQTT is widely used because of efficient publish/subscribe architectures.

☁️ Edge and cloud telemetry

Telemetry CAN be processed locally or centrally.

Benefits of Edge Computing:

• Lower Latency
• Less network load
• Higher availability
• Local real-time analysis

Cloud environments are more often used for:

• Big data analytics
• AI training
• Long-term storage
• Central dashboards

🧠 Telemetry and Industrial AI

Telemetry provides the data source for Industrial AI applications.

Applications:

AI systems analyse telemetry data for patterns and deviations.

🚗 Telemetry in AGVs and robots

Within AGVs and Robot systems, telemetry collects, among other things:

Real-time telemetry supports fleet management and predictive maintenance.

🛡️ Telemetry and Cybersecurity

Telemetry plays an important role within OT cybersecurity.

Applications:

Telemetry frequently feeds:

• SIEM
• SOC
• IDS
• SOAR
• Threat Intelligence platforms

🔐 Cybersecurity risks

Because telemetry systems process large amounts of operational data, risks arise.

Within critical infrastructures, manipulation of telemetry can have major operational consequences.

🔒 Security measures

Recommended measures for telemetry systems:

Many organisations implement security guidelines from IEC 62443.

⚡ Performance requirements

Telemetry systems must meet several technical requirements.

Large industrial environments often generate millions of telemetry events per day.

🌐 Telemetry within Industry 4.0

Telemetry forms a foundational layer for smart factories.

Important integrations:

Telemetry connects physical production processes to digital analytics systems.

📈 Benefits of telemetry

Key benefits:

• Real-time insight
• Higher availability
• Faster fault detection
• Predictive maintenance
• Improved process optimisation
• Better decision-making
• Lower operational costs

Telemetry also supports:

• LEAN
• Condition Monitoring
• Asset Management
• Smart manufacturing

⚠️ Challenges

Important challenges:

Within complex OT environments, telemetry often requires advanced architectures.