Title :
The ANN (assistant naval navigator) system
Author :
Rogers, C. David ; Hudak, J.J.
Author_Institution :
Collaborative Technol., Inc. (CTI), Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
The recreational boating community has always been plagued with a high incidence of serious accidents that have resulted in loss of life, grave injuries and property loss. Our paper discusses a next generation system enterprise that will apply a knowledge/cybernetic approach that provides: 1) An automatic Proactive Warning for severe navigation threats to participating operators of recreational and small commercial boats, followed by, and after operator acknowledgement, 2) An advisory threat evasive course/action. From our analyses of several years of USCG boating accident statistics, we expect that the system will reduce fatalities and serious injuries by about 30%.
Keywords :
boats; injuries; marine accidents; marine engineering; marine safety; navigation; statistical analysis; ANN; USCG boating accident statistics; advisory threat evasive course/action; assistant naval navigator system; automatic proactive warning; commercial boat; fatalities; grave injuries; knowledge/cybernetic approach; navigation threat; next generation system enterprise; property loss; recreational boating community; Accidents; Artificial neural networks; Boats; Instruments; Navigation; Security; Servers; ANN System; Emergency Response Unit; Interfaces; Local and State Jurisdiction; Proactive Warning; Towboat US;
Conference_Titel :
Homeland Security (HST), 2012 IEEE Conference on Technologies for
Conference_Location :
Waltham, MA
Print_ISBN :
978-1-4673-2708-4
DOI :
10.1109/THS.2012.6459860