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Sensing Engine

Capturing Condition, Environment and Performance
The Sensing Engine captures the condition, environment, performance and operational state of assets, equipment, processes and facilities.

Core Sensing Categories

Environmental
Temperature, humidity, gases, particles, noise, weather and air quality

Equipment condition:
vibration, acoustics, temperature, pressure, electrical and lubricant measurements

Process:
Flow, level, pressure, temperature, speed, position, torque and chemical measurements

Structural/geotechnical
Strain, displacement, tilt, acceleration, settlement, vibration and moisture

Energy/utilities
Electricity, water, gas, steam and compressed-air consumption

Safety and quality
Wearables, gas detection, machine vision, thermal imaging and inspection systems

From Measurement to Meaning

Sensor data alone does not create operational value. Measurements must be associated with the correct asset, location, process, operating context and history. The Sensing Engine therefore works closely with Identification and provides the foundation for AI-supported anomaly detection, prediction, risk prioritization and recommendations.

Edge and Enterprise

Edge computing can filter data, run local models, generate alerts and maintain selected functions when connectivity is limited. Enterprise platforms can aggregate information across equipment, sites and regions for analysis, benchmarking and planning.

Integration

Integration can use interfaces such as MQTT, OPC UA, Modbus, industrial Ethernet and REST APIs to exchange information with SCADA, PLCs, historians, MES, ERP, CMMS, EAM, QMS, building-management, fleet and digital-twin systems. Interface selection depends on the connected equipment and application.

Frequently Asked Questions

What can the Sensing Engine monitor?

It captures environmental conditions, equipment health, process variables, structural or geotechnical conditions, resource consumption, and safety or quality measurements. Sensor selection depends on the asset, operating environment and application.

Edge systems can filter and retain measurements, run local models and maintain selected functions when connectivity is limited. Data can synchronize with enterprise platforms when the connection is restored. The functions retained locally depend on the system design and application.

Next Steps

Continue to the AI Decision Engine to see how measurements and operational context support analysis and recommendations, or step back to the Identification Engine to review how measurements are associated with the correct asset. View  overview and applications of Physical AI and AIoT Engines for a synopsis or visit Physical AI and AIoT Architecture page to how all four engines are structured together, or visit Physical AI & AIoT Companies to see more applications in various industries.