Machine Learning and IoT Trends for Intelligent Prediction of Aircraft Wing Anti-Icing System Temperature

Airplane manufacturers are frequently faced with formidable challenges to improving both aircraft performance and customer safety. Ice accumulation on the wings of is one challenges, which could result in major accidents a reduction aerodynamic performance. Anti-icing systems, use hot bleed airflow from engine compressor, considered most significant solutions utilized applications prevent ice accumulation. In current study, novel approach based machine learning (ML) Internet Things (IoT) proposed predict thermal characteristics partial span wing anti-icing system constructed using NACA 23014 airfoil section. To verify strategy, obtained results compared those computational ANSYS 2019 software. An artificial neural network (ANN) used build forecasting model temperature experimental data fluid dynamics (CFD) data. addition, ThingSpeak platform applied this article realize concept IoT, collect measured data, publish private channel. Different metrics, namely, mean square error (MSE), maximum relative (MAE), absolute variance (R2), evaluate prediction model. Based indices, prove efficiency ANN IoT designing numerical CFD method, consumes lot time requires high-speed simulation devices. Therefore, it suggested that ANN-IoT be aviation.