Artificial Intelligence is the ability to transfer logical and cognitive schemes to artificial structures capable of learning from past experiences, in order to make optimal decisions.
Artificial Intelligence represents an essential tool for the real-time analysis of physical systems and the identification of the winning strategy, both for automated management and for Decision Support Systems (DSS).
The Idea-Re data science team comprises physicists and engineers and is directed by a full professor of Measurements.
Innovative A.I. algorithms for real-life applications developed by Idea-Re:
- Non-invasive measuremets for characterization of Hermetia Illucens (BSF) life cycle in rearing plant
- Real-Time Oil Leakage Detection on Aftermarket Motorcycle Damping System with Convolutional Neural Networks
- Comparison between Finite Elements simulation of residual stress and Computer Vision measurements in a welding TIG process
- Towards the development of a smart fused filament fabrication system using multi-sensor data fusion for in-process monitoring
- smart agriculture
- Edge Intelligence with Deep Learning in Greenhouse Management
- Anomaly detection in plant growth in a controlled environment using 3D scanning techniques and deep learning
- Neural network models for soil moisture forecasting from remotely sensed measurements
- Analysis of the effects of uncertainties on agrometeorological models
- Combining satellite data and Machine Learning techniques for irrigation Decision Support Systems
- smart city and smart land
- Snow water equivalent (SWE) measurements for better management of water resources to reduce drought risk
- Rivers’ Water Level Assessment Using UAV Photogrammetry and RANSAC Method and the Analysis of Sensitivity to Uncertainty Sources
- A Decision Support System Based on Rainfall Nowcasting and Artificial Neural Networks to Mitigate Wastewater Treatment Plant Downstream Floods
- Designing Air Quality Monitoring Systems in Smart Cities
- Design of an Urban Monitoring System for Air Quality in Smart Cities
- An Artificial Neural Network-based Real Time DSS to Manage the Discharges of a Wastewater Treatment Plant and Reduce the Flooding Risk
- Run-time optimisation of sewer remote control systems using genetic algorithms and multicriteria decision analysis: CSO and energy consumption reduction
- A life-cycle approach for multi-objective optimisation in building design: methodology and application to a case study
- A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings