Best Poster Award for energy monitoring research

(19-10-2016) Researchers from IDLab have received a Best Poster Award at 3rd European Workshop on Non-Intrusive Load Monitoring 2016 in London.

Non-intrusive load monitoring (NILM) refers to the disaggregation of sensor-based energy measurements that are collected at a single, centralized point in the home. By making use of advanced data analytics and machine learning algorithms, it is possible to deduce in real-time which household appliances are being activated, based on the detection and recognition of their unique fingerprint. This allows residents to obtain real-time insight into their energy consumption and makes them aware of dormant appliances.

The basic functionality of NILM has been researched for quite a while in controlled environments. However, disaggregation of complex appliances in a noisy environment and with many loads switching on and off independently remains challenging. IDLab has contributed to the development of new fine-grained energy monitoring technology that makes it possible to improve the performance and robustness of appliance disambiguation significantly.

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