Solving Today’s Challenges, Building Tomorrow’s Machinery

Reality-Connected Digital Twins Technology

The Digital Twin Problem: Traditional simulations, based on design specifications, can drift from reality because they are not connected to actual operational data.

Introducing Reality-Connected Digital Twins

  • Highly accurate, physics-based model of your machine that continuously corrects itself using sensor data from the actual operating machine, enabling Virtual Sensors.
  • The Power of Virtual Sensors: Digital sensors that estimate important internal conditions that are difficult or impossible to measure directly with physical sensors.
  • Hidden state estimation includes forces, internal wear, hydraulic leaks, loads and payloads, component fatigue and strain, among other unknown measurements.

Data-Driven Estimation: The Key to Unlocking Hidden Insights

Physical sensors are expensive, challenging to maintain, and limited in scope. Measuring critical parameters like internal forces, structural stresses, and wear is either impossible or too costly. 

Our Data-Driven Estimation solution uses upgraded simulation models and virtual sensors to estimate these hard-to-measure parameters.

By combining real-time sensor data with physics-based simulations, we provide insights into your machines’ internal behavior—without the need for additional sensors.

  • Cost Efficiency: Replace expensive physical sensors with reliable virtual counterparts.
  • Deeper Operational Understanding: Estimate structural loads, internal forces, stress points, and payload distribution.
  • Optimized Design and Operation: Use the insights to reduce failures and malfunctions, and extend machine operational time.
the concept of managing construction equipment and an excavator without human intervention using future technologies and artificial technology, eliminating errors and reducing the cost of work

Monitoring Machine Health: Building the Foundation for Smarter Maintenance

Unplanned downtime and reactive maintenance lead to excessive costs and operational inefficiencies. Current systems often fail to provide actionable diagnostics or meaningful data for condition-based maintenance planning.

With Monitoring Machine Health, we upgrade simulation models to monitor real-time operational parameters and detect anomalies.

This solution focuses on gathering accurate data and identifying risks to enable better maintenance workflows.

  • Real-Time Diagnostics: Identify deviations from normal operating conditions, such as excessive loads or abnormal actuator performance.
  • Anomaly Detection: Detect early signs of wear or stress before they escalate into costly failures.
  • Data Collection: Log operational and maintenance data to prepare for future predictive maintenance capabilities.
Wheel loader. X-ray render

Safety Data Fleet: Elevating Safety Across Your Fleet

Managing safety and performance across an entire fleet is challenging. Operators often lack visibility into unsafe operations, compliance reporting is tedious, and accidents result in high costs and operational delays.

Our Safety Data Fleet solution aggregates real-time data from all machines in a fleet, enabling proactive safety management and operational optimization.

With advanced monitoring and reporting tools, this solution helps operators and managers mitigate risks and enhance compliance.

  • Fleet-Wide Safety Monitoring: Track unsafe conditions like overloading, unstable inclinations, or high-speed operations across all machines.
  • Real-Time Feedback: Reduce accidents by alerting operators to unsafe behaviors, allowing them to adjust mid-operation.
  • Automated Compliance Reporting: Generate safety reports and logs for regulatory adherence without additional manual effort.
operation of an excavator without human intervention, remote control using artificial intelligence and monitoring the environmental impact of construction on the environment

Our Vision

Berrytron's ultimate vision is to make machines more intelligent, with higher levels of self-awareness and autonomy, thereby creating safer and more productive environments for machine operators.