EciDA: Evolutionary Changes in Distributed Analysis

The objective of this TKI proposal is: to develop and set up an IoT and (big) data-driven analysis platform that enables on-the-fly changes of data sources and changing data analysis steps and parameters over time to adapt to the changing environmental situation.

Background

Recent research shows that data growth has been exponential in many organisations in recent years. The information, which is relevant to the user, usually requires the processing of the entire historical data, together with the data available in real-time. Only by having such information can very precise predictions be made. Distributed computing and data processing systems are used where a workload can no longer be efficiently covered by a single computer.

Aim of the project

The objective of this TKI proposal is: to develop and set up an IoT and (big) data-driven analysis platform that enables on-the-fly changes of data sources and changing data analysis steps and parameters over time to adapt to the changing environmental situation. Within the framework of the ECiDA - NWO proposal of RuG, CWI, TNO, Vitens and Ancormen, the research is aimed at a large-scale improvement of the data analysis of water quality (both historical and from sensors in real-time) and a better prediction of the control of water quality in relation to the different water demand and water use goals.

Usage

This project is relevant because the use of continuous IoT sensor data from the water supply networks offers great potential for significantly improving water quality control. It also offers promising business opportunities by providing data-driven analysis solutions that can adapt to external changes (environment, new production line in the smart industry, adjustment of products, etc.).