The decision | maker
Thanks to its system architecture and tools, it can react & interact to live data
coming from connected devices by taking the needed or defined decision to perform.
learning methodologies for pattern recognition including:
Lifecycle & artefacts
It has developed tools to maintain its lifecycle to continuously build and
update its data model for better prediction and analysis.
Sensing up to 13 dimension of millions of bytes.
Make data fusion and structuring metadata from raw data.
Robust data storage using industry standards database technologies.
Assisted dataset structuring and qualification with video and audio.
from the data
Training and improving of recognition model for motion, video or sound analysis
Automatic self-testing for self-verification and self-quality scoring
GAIA can dramatically improve experience of different IoT domains using all the best approaches from classical machine learning (ML) to artificial intelligence (AI):
- Ability to recognize various patterns in real-time from live data.
- Handling of predictive maintenance and machinery malfunction.
- Monitoring of system conditions and raising of generalized notification like “malfunction, error handling…"
- Ability to predict failures in complex industrial system.
- Introducing security and prediction aspects into IoT system typically in car accidents or anti-crime visual technologies.
- Ability to adapt its data patterns to continuously changing environmental conditions.