The Intelligent PREdictive Maintenance for Aquaculture Systems is a research project aiming to improve the performance of aquaculture farms by introducing a novel platform and service for Intelligent predictive maintenance. The platform is based on innovative monitoring systems and smart infrastructure, relying on machine learning (ML) and artificial (AI) intelligence techniques. The platform measures key parameters in real time, introducing innovative multi-sensor gauges which feed a chain of ML models for Time Series Forecasting (TSF), Anomaly Detection (AD), Fault Classification (FC) and Remaining Useful Life (RUL) estimation. The measurements give the current health status of the farm site while the forecasts provide a glimpse of future status; analysis of the predictions allows identifying the potential need of preventive/corrective maintenance. A cloud-based integration of the different components of the platform allows improving connectivity and safety while optimizing the business process which lets the farmers benefit from a tailor made Software as a Service solution. To develop a platform and service for Intelligent predictive maintenance of aquaculture systems relying on machine learning and artificial intelligence techniques. The proposed predictive maintenance will be based on IoT and AI (i.e. sensors integrated “in” the structures), relying on new generation sensor technologies that allow redundant and robust monitoring of the status.

Website: https://agile.ro/iPREMAS/

Social Media: https://twitter.com/iPREMASproject