The National Shipbuilding Research Program (NSRP) has announced three project selections valued at over $6.2M in government and industry cost share funding. One of these is a project to further develop the I.M.SAFE AI-based fire prevention system that has been under development by MACSEA and PacMar Technologies under a Joint Development Agreement. Other team members […]
Last year, MACSEA Ltd and PacMar Technologies formed a strategic partnership to develop advanced infrared monitoring technologies for fire prevention in marine and industrial applications. Through a Joint Development Agreement, the two companies recently filed a provisional patent application for a Fire Monitoring and Detection System.
MACSEA Ltd, an industry pioneer in advanced monitoring systems, and PacMar Technologies, a leading innovator in marine and energy solutions, are excited to announce a strategic partnership to develop cutting-edge infrared monitoring technologies. This collaboration aims to enhance shipboard safety, especially with the presence of Lithium-Ion batteries, as well as shipyard safety pertaining to fire […]
MACSEA and its development partner, PacMar Technologies, recently completed an ONR-funded research project to develop technology for monitoring battery rooms on all-electric ships and issuing early warning alarms at the slightest increase in battery temperatures. The system uses both images and temperature data supplied by thermal cameras, along with AI-based algorithms, to automatically detect evolving […]
MACSEA is pleased to announce that Kevin Logan has completed all requirements to become a Certified RapidMiner Analyst. Logan has over six years of experience using RapidMiner software for artificial intelligence, machine learning, and predictive modeling R&D. Click here to download our Data Mining Capabilities.
Sensors are the eyes and ears of your automation. Their health is essential to all shipboard monitoring and control functions that require reliable data to synthesize decisions. In Part 2 of this series, we present some advanced research involving two multivariate machine learning algorithms; nonlinear state estimation and support vector machines, both applicable to shipboard […]
Sensors are the eyes and ears of your automation. Their health (i.e. accuracy and reliability) is essential to all shipboard monitoring and control functions that require reliable data to synthesize decisions, which pretty much includes everything. What is surprising is that, even with this critical role in machinery control, sensor health has received scant attention […]
