AI Case Study
CARFIT is offering real time issue detection on tires, wheels, shocks and brakes with machine learning
CARFIT, an AI startup providing vibration-based predictive maintenance for cars, has joined the NVIDIA Inception program and will be preparing a monitoring solution for wearing parts based on machine learning. This collaboration will enable the startup to enhance its technical knowledge and accelerate their development of Noise Vibration Harshness (NVH) products.
Consumer Goods And Services
Automobiles And Parts
"CARFIT’s core technology uses machine learning to leverage the car vibration NVH science [Noise Vibration Harshness – the science about vibrations and noises in vehicles] to identify wear and potential failures of the wearing parts of the driving gears of a vehicle. The result is an easy-to-use software module that adds NVH computing capacities and access to a NVH knowledge base to identify abnormal vibrations.
CARFIT is currently (January 2018) delivering a first aftermarket solution that addresses needs of cars in circulation. While building up its predictive maintenance knowledge base, CARFIT prepares a Machine-Learning-powered solution to uniquely monitor wearing parts such as tires, wheels, shocks and brakes of autonomous cars.
CARFIT will use NVIDIA® DRIVE series to offer an NVH analysis module software for autonomous vehicles."
Planned; results not yet available
"CARFIT leverages NVIDIA onboard compute to run Machine Learning for real time issue detection on tires, wheels, shocks and brakes."
"CARFIT revolutionizes the car service industry by combining NVH science (noise vibration harshness) with Artificial Intelligence to create individualized predictive car maintenance solutions.
According to Henri-Nicolas Olivier, CEO of CARFIT: 'Autonomous cars will need “autonomous maintenance” or predictive diagnostics to guarantee its users service level agreements in safety and comfort. CARFIT is growing up to serve this need.'"