S
Sauro Longhi
Researcher at Marche Polytechnic University
Publications - 396
Citations - 6208
Sauro Longhi is an academic researcher from Marche Polytechnic University. The author has contributed to research in topics: Fault detection and isolation & Control theory. The author has an hindex of 37, co-authored 385 publications receiving 5520 citations. Previous affiliations of Sauro Longhi include University of Rome Tor Vergata.
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Journal ArticleDOI
A Framework for Simulation and Testing of UAVs in Cooperative Scenarios
TL;DR: A framework for simulation and testing of UAVs in cooperative scenarios is presented, based on modularity and stratification in different specialized layers, which allows an easy switching from simulated to real environments, thus reducing testing and debugging times, especially in a training context.
Proceedings ArticleDOI
Physical rehabilitation exercises assessment based on Hidden Semi-Markov Model by Kinect v2
Marianna Capecci,M. G. Ceravolo,Francesco Ferracuti,Sabrina Iarlori,Ville Kyrki,Sauro Longhi,Luca Romeo,Federica Verdini +7 more
TL;DR: This work investigates how Hidden Semi-Markov Model can be used to monitor and evaluate physical rehabilitation exercises by Kinect v2 to support medical personnel and patients during rehabilitation at home and gives a feedback to physiotherapists and patients about exercise execution.
Journal ArticleDOI
A Database-Centric Framework for the Modeling, Simulation, and Control of Cyber-Physical Systems in the Factory of the Future
TL;DR: This article proposes database-centric technology and architecture that aims to seamlessly integrate networking, artificial intelligence, and real-time control issues into a unified model of computing.
Proceedings ArticleDOI
On line solar irradiation forecasting by minimal resource allocating networks
TL;DR: An on-line prediction algorithm to estimate, over a determined time horizon, the solar irradiation of a specific site and is able to avoid the initial training of the neural network is described.
Proceedings ArticleDOI
Multi-scale PCA based fault diagnosis on a paper mill plant
TL;DR: Multi-Scale Principal Component Analysis (MSPCA) is used to monitor some critical variables of the stock preparation of a paper mill plant in order to diagnose faults and malfunctions.