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 […]
https://macsea.com/wp-content/uploads/NSRP-Logo.png157249macseahttps://macsea.com/wp-content/uploads/Macsea-primary.svgmacsea2025-10-08 12:01:292025-10-08 12:01:30MACSEA Team Selected for National Shipbuilding Research Program R&D Funding
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.
https://macsea.com/wp-content/uploads/battery-fire.webp6651280macseahttps://macsea.com/wp-content/uploads/Macsea-primary.svgmacsea2025-07-24 16:29:522025-07-25 13:15:28MACSEA and PacMar Patent Pending for Fire Prevention 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 […]
https://macsea.com/wp-content/uploads/LIB-IR.png243164macseahttps://macsea.com/wp-content/uploads/Macsea-primary.svgmacsea2024-05-18 09:44:472024-05-18 16:56:18Reducing Risk of Battery Fires on Ships
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.
According to some industry estimates, hull and propeller performance degradation can cause fuel penalties in the range of 15 to 20 per cent, with a corresponding increase in GHG emissions. Diligent hull condition monitoring and maintenance can negate these penalties and represents an effective, low-cost energy saving measure available to ship owners for immediate implementation.
The Diesel Expert software accepts data inputs from cylinder combustion analyzers and automatically diagnoses any existing engine faults. Diesel Expert contains expert-level diagnostic intelligence in the form of an embedded neural network that has been trained to recognize symptoms associated with various engine problems.
A new white paper is available describing a business case study for our Hull Medic hull condition monitoring service. The business case is based on a customer’s pilot study to evaluate the anti-fouling effectiveness of alternative hull coatings.
https://macsea.com/wp-content/uploads/steth.jpg129172macseahttps://macsea.com/wp-content/uploads/Macsea-primary.svgmacsea2012-11-14 09:19:462025-07-10 17:10:19Ship Hull Condition Monitoring Fouling Detection White Paper Available
MACSEA’s Fuel Vision system now works with Emerson’s Micro Motion Coriolis® flow meters for high-accuracy fuel monitoring to help ship operators quantify the real effects of various energy conservation measures.
The marine industry is increasingly adopting Condition-Based Maintenance (CBM) as cost-effective strategy for Reduced Total Ownership Cost, fostering the approach of performing maintenance only when objective evidence of need exists. However, because of the special skills and time required to implement CBM, particularly as ship systems become more complex, future ship systems should employ artificial […]
https://macsea.com/wp-content/uploads/code-ship.jpg11212000macseahttps://macsea.com/wp-content/uploads/Macsea-primary.svgmacsea2012-07-30 17:49:472025-07-10 17:10:28Teaching Computers to Think Like Engineers
MACSEA Team Selected for National Shipbuilding Research Program R&D Funding
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 […]
MACSEA and PacMar Patent Pending for Fire Prevention System
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 and PacMar Technologies Announce Partnership to Develop Advanced Infrared Monitoring Technologies
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 […]
Reducing Risk of Battery Fires on Ships
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 Data Scientist Receives Certification
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.
Controlling Ship Hull Fouling Helps Save Fuel
According to some industry estimates, hull and propeller performance degradation can cause fuel penalties in the range of 15 to 20 per cent, with a corresponding increase in GHG emissions. Diligent hull condition monitoring and maintenance can negate these penalties and represents an effective, low-cost energy saving measure available to ship owners for immediate implementation.
DEXTER Diesel Expert™ Module Helps Keep Engines Fuel Efficient
The Diesel Expert software accepts data inputs from cylinder combustion analyzers and automatically diagnoses any existing engine faults. Diesel Expert contains expert-level diagnostic intelligence in the form of an embedded neural network that has been trained to recognize symptoms associated with various engine problems.
Ship Hull Condition Monitoring Fouling Detection White Paper Available
A new white paper is available describing a business case study for our Hull Medic hull condition monitoring service. The business case is based on a customer’s pilot study to evaluate the anti-fouling effectiveness of alternative hull coatings.
High-Accuracy Fuel Monitoring with Fuel Vision
MACSEA’s Fuel Vision system now works with Emerson’s Micro Motion Coriolis® flow meters for high-accuracy fuel monitoring to help ship operators quantify the real effects of various energy conservation measures.
Teaching Computers to Think Like Engineers
The marine industry is increasingly adopting Condition-Based Maintenance (CBM) as cost-effective strategy for Reduced Total Ownership Cost, fostering the approach of performing maintenance only when objective evidence of need exists. However, because of the special skills and time required to implement CBM, particularly as ship systems become more complex, future ship systems should employ artificial […]