Name
Title | ||
|---|---|---|
Artificial Intelligence - Based Measurement Systems for Automotive: a Comprehensive Review |
Abstract | ||
|---|---|---|
The development of ever intelligent systems in various application fields is nowadays a hot research topic. Artificial Intelligence (AI) techniques become a key enabler of the transition between classical static, hard-coded algorithms and innovative, flexible ones. Actually, the automotive sector can undoubtedly benefit from the usage of the aforementioned techniques, aiming at building a novel smart automotive industry. Indeed, the application of AI spreads all round the automotive sector, ranging from on–board measuring systems to customer satisfaction analysis and demand prediction. This paper aims to review the possible applications of Artificial Intelligence techniques to the automotive sector, with a special focus on innovative measurement systems and metrology. Indeed the focus will be, between others, on Advanced Driver Assistance Systems (ADAS), in-vehicle IoT systems and intelligent industrial measuring systems, thus allowing to both increase road safety and design accurate predictive maintenance, additive manufacturing systems and, in substance, to build the smart automotive factory of the future. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/MetroAutomotive54295.2022.9855154 | 2022 IEEE International Workshop on Metrology for Automotive (MetroAutomotive) |
Keywords | DocType | ISBN |
Artificial Intelligence (AI),Machine Learning (ML),ADAS,Driving Automation,ACC,Driving Automation System (DAS),Internet of Vehicles (IoV) | Conference | 978-1-6654-6690-5 |
Citations | PageRank | References |
0 | 0.34 | 21 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tommaso Fedullo | 1 | 0 | 1.35 |
| Alberto Morato | 2 | 0 | 1.35 |
| Federico Tramarin | 3 | 0 | 0.34 |
| Stefano Cattini | 4 | 0 | 0.34 |
| Luigi Rovati | 5 | 0 | 0.34 |