AI Case Study
CMA CGM enhances its cargo ships piloting and collision avoidance techniques through real time object detection
CMA CGM has collaborated with Shone to deploy an AI-powered system designed to aid crew members, support operations and optimise situational awareness and navigation. Bridge navigation sensors and installed cameras feed the system with data which it then analyses to avoid collisions and automate piloting. The startup uses machine learning to for detecting objects in real time.
Freight And Logistics
"CMA CGM and Shone collaborated to create and deploy a system to improve situational awareness, streamline bridge operations and enhance safety of navigation. The system fuses data from bridge navigation sensors and installed cameras and employs advanced artificial intelligence (AI) techniques taking into account the COLGREG rules to give bridge watchstanders an important decision-making support tool for piloting and collision avoidance.
“The pilot program validated the feasibility and value of retrofitting existing ships with technology to provide assistance to the navigation crew,” said Shone co-founder Clement Renault. “Artificial intelligence and machine learning techniques have been used to perform object detection in real time and augment the information already available from standard sensors such as AIS and radar.”" (maritime-executive.com)
"Shone aims to modernize shipping. The startup applies NVIDIA GPUs to a flood of traditional cargo ship data such as sonar, radar, GPS and AIS, a ship-to-ship tracking system. This has enabled it to quickly process terabytes of training data on its custom algorithms to develop perception, navigation and control for ocean freighters. The company has added cameras to offer better seafaring object detection as well.
“What is particularly interesting for CMA CGM is what artificial intelligence can bring to systems on board container ships in terms of safety. AI will facilitate the work of crews on board, whether in decision support, maritime safety or piloting assistance,” said Jean-Baptiste Boutillier, deputy vice president at CMA CGM." (nvidia)
Pilot; results not yet available
"Artificial intelligence and machine learning techniques have been used to perform object detection in real time"
Data from bridge navigation sensors and installed cameras