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 thermal threats and issue alerts to sailors long before the temperature of any battery becomes a problem. Read More
The Archives
Browse the content below to find what you're looking for.
Reducing Risk of Battery Fires on Ships
Saturday, May 18th, 2024MACSEA Data Scientist Receives Certification
Monday, January 15th, 2018
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.
Sensors – The Eyes and Ears of Ship Automation – Part 2
Wednesday, June 13th, 2012Sensors 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 sensor diagnostics. Data collected from a ship’s main propulsion gas turbine engine is used in the case study.
Sensors – The Eyes and Ears of Ship Automation – Part 1
Monday, May 14th, 2012Sensors 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 in the marine industry. In fact, they represent the weak link in modern automation and control systems, from both a safety and a health monitoring perspective.