The partners of OPENTUNITY are working on the development of Artificial Intelligence-based Non-Intrusive Load Monitoring (NILM) algorithms. This groundbreaking technique allows for the meticulous observation of energy consumption in buildings without the need for cumbersome hardware installations on individual appliances. This development will be tested in the Slovenian, Spanish and Swiss pilot sites.

The essence of these advanced algorithms lies in their ability to extract valuable insights from overall household energy consumption data. By leveraging this information, the algorithms can accurately infer the activities of active appliances and their corresponding energy usage at any given moment. What truly sets NILM apart is its capacity to provide detailed and disaggregated energy consumption insights, all achieved without the necessity of submetering. This not only simplifies the monitoring process but also translates into substantial cost savings for end-users.

In the pursuit of excellence, OPENTUNITY and its partners are actively engaged in comprehensive research, diligently assessing the State of the Art in the field. The focal point of their endeavors is the development of semi-supervised algorithms, a relatively unexplored territory in the Artificial Intelligence area. This innovative approach not only showcases their commitment to pushing boundaries but also positions them as pioneers in harnessing the full potential of AI for energy monitoring.

By embracing this promising approach, OPENTUNITY is set to usher in a new era of energy monitoring that is not only technologically advanced but also cost-effective, providing tangible benefits to end-users across Europe.

The next steps are to start looking for public datasets to start modelling the algorithms. Then, the idea will be to train the algorithms with data coming from the pilot sites.