The IntelliSense.io Virtual Sensor Portfolio is a software module that generates real-time, model-based outputs—known as virtual sensors—to deliver actionable insights into the performance of industrial processes and assets. Unlike traditional physical sensors, these virtual sensors use a combination of mechanistic (physics-based) models and machine learning to estimate key process variables and asset conditions that may be difficult or costly to measure directly. The outputs are presented through user-friendly dashboards and reports, enabling operators and decision-makers to monitor, analyze, and optimize operations in real time. This approach enhances visibility across the value chain, supports predictive maintenance, and improves process efficiency by providing a richer, more comprehensive view of operational data.

Key Features

Real-Time Model Outputs Delivers up-to-date virtual sensor data for process and asset monitoring.

• Provides continuous, high-frequency insights
• Reduces reliance on physical sensor infrastructure

Scientific AI Integration Combines physics-based models with machine learning for accurate predictions.

• Enhances trustworthiness of virtual sensor outputs
• Adapts to changing process conditions

User-Friendly Dashboards and Reports Visualizes virtual sensor data for actionable decision-making.

• Customizable dashboards for different user roles
• Automated reporting for operational transparency

Seamless Platform Integration Works within the IntelliSense.io platform and with other modules.

• Supports end-to-end process optimization
• Enables integration with reconciliation and data quality tools

Benefits

Enhanced Process Visibility Provides insights into variables not directly measured by physical sensors.

• Improves understanding of process dynamics
• Identifies inefficiencies and bottlenecks

Cost and Maintenance Reduction Minimizes need for additional physical sensors and associated upkeep.

• Lowers capital and operational expenditures
• Reduces downtime from sensor failures

Improved Decision-Making Enables data-driven operational and maintenance strategies.

• Supports predictive maintenance
• Facilitates proactive process adjustments