Department of Transportation · Federal Transit Administration
THE PURPOSE OF THIS CALL ORDER IS TO PROVIDE MACHINE LEARNING CONTRACT SUPPORT.
Department of Transportation
13 AI/ML contracts · $8.30M total awarded.
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Department of Transportation · Federal Aviation Administration
ARTIFICIAL INTELLIGENCE AND ADVANCED ANALYTICS TO ESTIMATE COLLISION RISK DURING DEPARTURE AND ARRIVAL
Department of Transportation · Pipeline and Hazardous Materials Safety Administration
PHMSA'S ARTIFICIAL INTELLIGENCE SUPPORT FOR RULEMAKING INITIATIVE
Department of Transportation · Federal Transit Administration
THE PURPOSE OF THIS CALL ORDER IS TO PROVIDE ARTIFICIAL INTELLIGENCE SUPPORT.
$500K
Department of Transportation · Federal Highway Administration
ARTIFICIAL INTELLIGENCE KNOWLEDGE & TECH TRANSFER STRATEGIES
$497K
Department of Transportation · Immediate Office of the Secretary of Transportation
SMALL BUSINESS INNOVATION RESEARCH (SBIR) FY22 PHASE 2 AWARD ON U.S. DOT SBIR TOPIC 22-FH2 FOR EDGE SERVER-BASED ARTIFICIAL INTELLIGENCE APPLICATION FOR DILEMMA ZONE & TRAFFIC CONFLICT EVENTS DETECTION
Department of Transportation · Federal Railroad Administration
THE OBJECTIVE OF THIS PROJECT IS TO DEVELOP AN INTELLIGENT RISK ASSESSMENT AND PREDICTION SYSTEM (I-RAPS) THAT WILL INTEGRATE SELF-LEARNING ARTIFICIAL INTELLIGENCE AND DEEP NEURAL NETWORK DECISION-MAKING MODELS, TRACK INSPECTION DATA, VEHICLE INFORMA
Department of Transportation · Federal Railroad Administration
IGF::OT::IGF - BROAD AGENCY ANNOUNCEMENT (BAA) 2017 FRA-TR-004 PREDICTIVE ANALYTICS TRACK INSPECTION OPTIMIZATION COST NO FEE R&D PROJECT ENTITLED "ARTIFICIAL INTELLIGENCE AIDED TRACK RISK ANALYSIS (AL-TRACK RISK)" IN ACCORDANCE WIT
Department of Transportation · Federal Railroad Administration
IGF::OT::IGF RAILROAD ARTIFICIAL INTELLIGENCE INTRUDER LEARNING SYSTEM (RAIILS) PROPOSAL FOR THE PROCESSING OF DATA FROM HETEROGENEOUS SENSING PLATFORMS FOR THE PURPOSE OF IMPROVED DETECTION OF RAILROAD TRESPASSERS IN REAL-TIME USING CONVOLUTIONAL NEURAL NETWORKS (CNNS). FOR A SYSTEM EQUIPPED WITH CO-LOCATED NATURAL COLOR RED/GREEN/BLUE (RGB) AND THERMAL INFRARED CAMERAS, WE PROPOSE A DEEP LEARNING AI ARCHITECTURE TO DO ON-PLATFORM SENSOR FUSION. SUCH A SYSTEM WILL ALLOW FOR THE DETECTION OF RAILROAD TRESPASSERS BOTH IN REAL-TIME AND DURING THE ENTIRE 24HR CYCLE. THE PROPOSED ARCHITECTURE WOULD LEVERAGE BOTH THE RGB AND INFRARED DATA WHEN AVAILABLE AND WOULD CHANGE TO INFRARED ONLY WHEN ENVIRONMENTAL/TIME-OF-DAY CONDITIONS DO NOT PERMIT THE USE OF THE VISIBLE-SPECTRUM DATA.
Department of Transportation · Federal Railroad Administration
THE OBJECTIVE OF THIS PROJECT IS TO DEVELOP A DATA ANALYSIS PLATFORM TO FACILITATE THE ASSESSMENT OF DEFECT DETECTION ON TRACK SYSTEMS BY (1) INVESTIGATING MACHINE LEARNING TECHNIQUES TO ENHANCE AUTOMATION AND FACILITATE REDUCED MANUAL LABOR FOR TRAC
Department of Transportation · Federal Railroad Administration
DEVELOP I-ASAP FOR CONTINUOUS, REAL-TIME MONITORING AND RECOGNITION BASED ON ADVANCED COMPUTER VISION AND IMAGE ANALYSIS, ARTIFICIAL INTELLIGENCE (AI), EDGE COMPUTING, AND INFORMATION SHARING WITH BOTH LOCAL LAW ENFORCEMENT AND RAILROADS THROUGH SE
Department of Transportation · Federal Highway Administration
THE PURPOSE OF THIS REQUISITION IS FOR THE PURCHASE OF THE GOOGLE CLOUD PLATFORM, PROVIDING A SUITE OF COMPUTING, DATA STORAGE, DATA ANALYTICS, MACHINE LEARNING, AND COMPREHENSIVE MANAGEMENT TOOLS, ENSURING SCALABILITY, SECURITY, AND COMPLIANCE WITH
Department of Transportation · Federal Railroad Administration
THIS BROAD AGENCY ANNOUNCEMENT (BAA) SUPPORTS THE U.S. DEPARTMENT OF TRANSPORTATION (DOT), OFFICE OF RESEARCH, DATA, AND INNOVATION (RDI) TO SERVE THE RAIL INDUSTRY BY IDENTIFYING LEVERAGE POINTS FOR ARTIFICIAL INTELLIGENCE (AI) TOOLS AND CHANGES TO