ERCET is about earth, wind and water

The mission of this ERCET value area is to build the world’s largest energy & sensor data hub: the internet-of-things. 

Activities will center on efficient storage and retrieval of data from large, multi-sensor networks, failure management, anomaly detection, historical comparison using machine learning, real-time pattern recognition and artificial intelligence. Concrete goals include the following:
 

  • Set up an R&D center, which will facilitate the creation of local expertise and high-impact services in the fast-growing field of ubiquitous sensing;
  • Set up the Sensor data hub platform;
  • Collect and analyze energy data;
  • Collect and analyze seismic data;
  • Use the R&D center as a development environment for the recently initiated Dike Data Service Center (DDSC, see www.ddsc).

 

Value area: water & climate

Focus 1

Partners will develop an energy platform with smart algorithms that can collect and process in near real-time energy production and consumption data from thousands of households. The data will be used to monitor the electricity grid, improve individual and corporate awareness of energy consumption, promote energy saving, and stimulate energy trade. In addition, issues of privacy, authentication, identification and security will be explored together with other public and private partners. At the same time, innovative ICT applications and services (running on the shared ICT infrastructure) will be interfaced with SME partners' energy-related products and systems.

 

Focus 2 and 3

A second major focus within this federation is to create an R&D center, which will facilitate the creation of local expertise and high-impact services in the fast-growing field of ubiquitous sensing. Seismic data in the north of the Netherlands provided by partners like TNO and other local SME’s will be collected and analyzed. The center will also serve as a business development environment for the recently initiated Dike Data Service Center (DDSC). Activities will center on efficient storage and retrieval of data from large, multi-sensor networks, failure management, anomaly detection, historical comparison using machine learning, real-time pattern recognition and artificial intelligence.

The third major focus is valorization. In this case: translating new knowledge on energy and sensor data into new staff positions within participating local SME’s and new spin-off companies.

 

A practical example: 55% of the Dutch population is located in areas prone to large-scale flooding. Researchers at ERCET are expected to develop cognitive algorithms to simulate rainfall and its impact on dykes and the coastline to prevent major flooding.