AI monitoring systems
Lack of monitoring and control
Problem
Unreliable facility processes data
Irregular data registration
Rare data registration
Lack of indexes evaluated
Factors:
Measurement units irrelevance
Lack of automated registration
Registration errors
Falsification of data
Contradictory information
Risks:
Outdated information
Lack of reliable information
Lack of reliable data affects on planning and decision-making performance
Innovative monitoring practices
Solution
Automotive monitoring and analytics tools
Detection of many types of objects with computer vision algorithms
Detection of stable and moving objects
Automated indexes evaluation and calculation of aggregated ratios
Capabilities:
Real-time reports generation
Integration with internal and external databases
Detected objects characteristics: quantity, volume, color, speed
Defectoscopy and fault detection
Objects morphology analyses
Indexes:
Process KPI analyses
Facility processes analyses, bottleneck indication
Strategy analyses, forecasting, scenario analyses
Recognition system
Artificial intelligence by Leonovich Labs
Real-time analytics and reports generation
Scanning of objects
With a camera above
Dataset update
Automatically on regular biases
Individual learning
On facility processes
Indexes customization
For any type of reports
Scanning of objects
Recognition system
Artificial intelligence by Leonovich Labs
Real-time analytics and reports generation
Automatically on regular biases
Dataset update
On facility processes
Individual learning
For any type of reports
Indexes customization
With a camera above
Cases of application

Waste monitoring on sorting stage example
Reports example
Contacts:
+7(929) 938 95-09
Catherine Loginova
Leonovich Labs project manager

+7(965) 422 45-59
Ivan Andreev
Leonovich Labs sales manager