Intelligent self-diagnostics
Provider: Technologická agentura České republiky
Programme: Doprava 2020+
Implementation period: 01.01.20 - 31.03.22
Workplace:
Dopravní fakulta Jana Pernera - Katedra informatiky a matem. v dopravě
Investigator: Kulička JiříTeam member: Jahodová Berková Andrea | Kašparová Miloslava | Petr Pavel
Description:
The aim of the project is to significantly speed up, reduce the cost and overall streamline of car diagnostics. Thanks to the involvement of mathematical, statistical and data mining methods, machine learning methods and artificial intelligence, the success of troubleshooting will increase significantly from today's usual 56% (controlled search method) to 97%. The project has a social dimension, as a significant part of the project results will be directly available to the general public in the specialized database FCD Portal. An effective way of diagnosing faults will result in a reduction in harmful emissions, which is associated with the operation of suboptimal cars. This reflects another societal need focused on the ecology of transport.
The aim of the project is to significantly speed up, reduce the cost and overall streamline of car diagnostics. Thanks to the involvement of mathematical, statistical and data mining methods, machine learning methods and artificial intelligence, the success of troubleshooting will increase significantly from today's usual 56% (controlled search method) to 97%. The project has a social dimension, as a significant part of the project results will be directly available to the general public in the specialized database FCD Portal. An effective way of diagnosing faults will result in a reduction in harmful emissions, which is associated with the operation of suboptimal cars. This reflects another societal need focused on the ecology of transport.
