Meet DIONE partner Sinergise (Watch Video)
December 23, 2021
Meet DIONE partner InoSens (Watch Video)
January 12, 2022
Watch the full video to learn more about Core Innovation and how the partner contributes to DIONE!
Core Innovation help the industry to attach meaning to their data using Artificial Intelligence so that they can unleash the power of their machines, make predictions about what is going to happen in the near future, and be prepared. To achieve that, Core Innovation make use of their customers’ experience, knowledge, and data.
Core Innovation tailor-made algorithms for multiple functionalities and use-cases in various industrial sectors, such as Industry 4.0 & Manufacturing, Energy (EeB, Smart Grids), Critical Infrastructure and Equipment, Smart Systems, and Personalisation, and Smart Cities and Communities. Thier services include data collection and labeling, data sensor visualization, anomaly detection, system interpretation, condition monitoring, process, quality, and maintenance predictions and analytics.
Through DIONE, Core Innovation will use their expertise in deep learning algorithms to design and develop an Environmental Impact Assessment Tool. The system will be proposed to identify and quantify the levels of some of the monitored parameters and to extract tangible environmental impact on a regional level.
Core Innovation tailor-made algorithms for multiple functionalities and use-cases in various industrial sectors, such as Industry 4.0 & Manufacturing, Energy (EeB, Smart Grids), Critical Infrastructure and Equipment, Smart Systems, and Personalisation, and Smart Cities and Communities. Thier services include data collection and labeling, data sensor visualization, anomaly detection, system interpretation, condition monitoring, process, quality, and maintenance predictions and analytics.
Through DIONE, Core Innovation will use their expertise in deep learning algorithms to design and develop an Environmental Impact Assessment Tool. The system will be proposed to identify and quantify the levels of some of the monitored parameters and to extract tangible environmental impact on a regional level.
