IoT and Advanced Data Analysis

Critical Materials actively engages in the interoperability of devices and sensors in order to enhance the health status of critical structures.

We have extensive experience with information systems that use models mimicking physical that are fed with sensor data. This requires the aggregation of raw sensor data to higher-value context information.

This IoT approach enables the support to our customer’s activities by aggregating and conveying information comprehensively for assisted decision making – whichever the context.

Combining database retrieval strategies dealing with massive data volumes, with and extensive data analytics toolset we are able to extract meaningful information at the end of the data pipeline.

With Critical Materials, Big data analytics meets physical structural complexity and materials engineering.


With Critical Materials, Big data analytics meets physical structural complexity and materials engineering.

We act upon all these vectors:

  • Edge connectivity – sensors and low level networks
  • Cloud Infrastructure- scalable computation
  • Cyber-physics – geometry and materials multi-physical models
  • Personalization – data analytics tailored to your problems

With this approach, Critical Materials is capable of integrating tailor made analysis into IoT platforms. Simultaneously,

Almost ten years of looking at volumes of data and extracting knowledge from it, gave us a solid background in the following areas:

  • Systems analytics: Multiple Input – Multiple outputs analysis;
  • Statistical analysis for outlier detection;
  • Predictive models;
  • Clustering;
  • Bayesian network analysis;
  • Search heuristics;
  • Dimensionality regression (Principal Components Analysis);

Our toolbox includes the R statistical package, Python language, Matlab Simulink and other custom made tools.