DyVerSIFy (2018 - 2019)
Dynamic Visualization, Adaptive Analysis and Scalability for Mining Sensor Data with Integrated Feedback
Intelligent monitoring for predictive maintenance
Sensors play an increasing role in monitoring the condition of train fleets. To mine the explosive amounts of collected sensor data, Televic GSP is investigating novel techniques in a new imec.icon research project.
Dynamic, adaptive and scalable sensor analytics
The new project, called DyVerSIFy, brings together industry players and research groups with different specializations. The aim is to improve dynamic visualization, adaptive anomaly detection and scalability.
The DyVerSIFy project will conclude in 2019. The insights will be used for the mechatronics solution.
The end goal of the DyVerSIFy project is to surmount the difficulties and complexities associated with the development of sensor data visualization and analytics systems. In doing so, the project will enable companies to gain even faster business insights, for informed decision-making and improved business processes.
Our project partners
The DyVerSIFy consortium consists of industry players and research groups specializing in sensor system design, intuitive visualization and anlytics software design, scalable software systems, semantics and machine learning.
Renson Ventilation, Cumul.io, IDLab UGent
ICON research projects are agile and demand-driven, combining academia and industry partners. ICON projects typically have a duration of two years, yet quickly adapt to the rapid-evolving digital landscape.
The DyVerSIFy project was co-funded by imec and by Flanders Innovation & Entrepreneurship