Title :
Artificial intelligence for explosive ordnance disposal system (AI-EOD)
Author :
Madrid, Ron ; Williams, Bob ; Holland, Joe
Author_Institution :
Los Alamos Nat. Lab., NM, USA
Abstract :
The artificial intelligence explosive ordnance disposal system (AI-EOD), developed in support of the Naval Explosive Ordnance Disposal Technology Center, is a neural network AI-based multiple-incident identification, recording, and tracking system featuring state-of-the-art search, retrieval, and image and text management. It is concluded that the AI-EOD has proven itself by meeting the goals established for it. The system separates the reasoning engine from the data. Using the system augments the abilities of both the less experienced and the seasoned technician. The AI-EOD does not require new training of veteran units and can be used in the training of new recruits. The maintenance ease and portability of the CD-ROM overcomes the problems with microfiche and paper. Testing and evaluation have shown that using the microfiche/paper-based identification system requires approximately 9.6 min to make a correct identification, while the AI-EOD system takes an average of only five minutes
Keywords :
artificial intelligence; image processing; information retrieval systems; neural nets; CD-ROM; artificial intelligence; explosive ordnance disposal system; image and text management; neural network AI-based multiple-incident identification; reasoning engine; retrieval; state-of-the-art search; tracking system; Artificial intelligence; Artificial neural networks; CD-ROMs; Engines; Explosives; Image retrieval; Management training; Recruitment; Technology management; Waste management;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.287182
