AI FOR INDUSTRY
sAIfer Lab research boosts industry maintenance processes with prescriptive analytics and optimizes transport in rail, aviation, and maritime sectors; it also supports Law Enforcement Agencies in preserving people safety in public places.
AI for Industry is a research area carried on by the sAIfer Lab, through SmartLab and Pra Lab both, altough the two labs work to solve different problems in different sectors.
The research activites conducted by the SmartLab since 2005 revolutionizes maintenance and transportation sectors by enhancing efficiency and safety.
For maintenance we focused on three main concepts:
- Condition Monitoring: Continuous monitoring of machinery health using sensors and AI analytics.
- Predictive Maintenance: AI predicts equipment failures before they happen, reducing downtime and costs.
- Prescriptive Maintenance: AI prescribes what need to be done to reduce failure, downtime and costs.
In particular, in the field of transportation, we focus on:
- Railway: AI optimizes scheduling, monitors track conditions, and predicts maintenance needs.
- Aviation: AI improves flight scheduling, fuel optimization, and predictive maintenance of aircraft.
- Maritime: AI enhances ship designs and predictive maintenance of vessels.
The research activites conducted by the Pra Lab since 2010, focus on Intelligent Video Surveillance applications aimed at supporting Law Enforcement Agencies (LEAs) in preserving people safety in public places.
In particular we work on two specific applications:
- Crowd counting and Density Estimation, to support LEAs in monitoring crowds, e.g., during mass gathering events.
- Person re-identification, to support forensic investigators in searching for suspect individuals over a large amount of video surveillance footage.
Research Topics
Active research projects
LAB DIRECTORS
Davide Anguita - Full Professor
Luca Oneto - Full Professor
Fabio Roli - Full Professor
RESEARCH DIRECTORS
Luca Demetrio - Assistant Professor
Giorgio Fumera - Associate Professor
FACULTY MEMBERS
Lorenzo Putzu - Assistant Professor
POSTDOCS
Rita Delussu
PhD STUDENTS
Irene Buselli
Emanuele Ledda
RESEARCH ASSOCIATES
Gianluca Boleto
Gianluca Sommariva