Ingenium will attend the International Conference on Integrated Emergin Methods of Artificial Intelligence & Cloud Computing (IEMAICLOUD), placed in London during April 26-29th. This conference is organizated by the Institute of Engineering & Management. The significant characteristic of IEMAICLOUD is the promotion of dialogue between scientists. researchers, engineers and corporates.

Ana Maria Peco has presented the article entitled “False Alarm Detection in Wind Turbine Management by K-Nearest Neighbors Model.” in the fields of alarm analysis, control monitoring and machine learning. Supervisory control and data acquisition systems are employed to monitor and control the condition of wind turbines. Machine learning algorithms process variety and a large volume of data from control monitoring systems. A real case study is presented with the dataset from a real wind turbine with the goal to detect false alarms. The novelty proposed in this paper is to use a K-nearest neighbor algorithm for the prediction and classification of false alarms. The holdout validation and k-fold validation have been evaluated for this algorithm.  The highest accuracy is obtained by weighted K-nearest neighbor with 5-fold validation, with a value of 98,7%. The specificity and the sensitivity are 88,52% and 99,13%, respectively. These values imply that the methodology used is effective for false alarm detection and identification.