The Air Force has a requirement, based on the Sikes Act and Air Force Instruction (AFI) 32-7064 and through their Integrated Natural Resources Management Plan (INRMP), to maintain the bases’ natural environment while still meeting military mission objectives. Natural Resource Managers (NRM) in the DoD achieve habitat and species sustainability through monitoring state endangered/species of concern. However, current species surveys are labor intensive, potentially inaccurate, and performed infrequently, thus impacting results and management planning. Our solution is to integrate two existing survey systems developed through two recent Phase II SBIRs into a hybrid dual-sensor system. The dual-sensor system combines machine vision (Cybernet) and acoustic (CTSi) sensors to produce species detection data. This data is processed and stored by a host computer programmed to conduct an automated and autonomous species population survey. Post-processing of the survey data can provide for automated species identification. The system has a 360? field of view and operates day and night. The integrated system will detect more species than either machine vision or acoustic identification alone, and produce a sharable database.

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