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04/06/2026

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Customized Machine Learning Models

Customized Machine Learning Models - 1

Service description

The service supports experimental development and testing of customized machine learning models for process monitoring and optimization. The work may include algorithms for time-series-based predictions in Buteo, such as growth rate and nutrient uptake, image analysis for foam detection and process monitoring, and predictive maintenance models for early warnings and alarm handling. The purpose is to help companies gain insight into data patterns and process anomalies and create a documented basis for further optimization, monitoring, and AI-enabled decision support.
Expected results: Documented insights into data patterns and process anomalies with reported model results and recommendations that can form the basis for future optimization, monitoring, or implementation of AI-based solutions.
Methodology: The service is delivered as an experimental development and analysis process including clarification of data and use case, development and testing of relevant machine learning models in the Biosolutions Lab, and delivery of documented results and recommendations for further use or optimization.
Target: Biosolutions, Biotechnological processes, Process monitoring, Predictive maintenance, Other emerging and enabling technologies
  • Organisation: DTI
  • Type: experiment
  • SUT/E: Machine learning models for time-series prediction, image analysis, and predictive maintenance in biosolutions and process environments
  • Average duration: 1-5 weeks
  • Contact: uln@teknologisk.dk

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