As processing and manufacturing facilities quickly progress from barcode to radio-frequency (RFID) and similar technologies to track the movements of resources (tools, parts, support equipment), many related opportunities to cut costs and increase safety by reducing human error are emerging. We propose to research and develop AreaAdvisor, an AI software system that manages this new tracking data, featuring an innovative spatial scheduler and data mining capabilities. AreaAdvisor will allow KSC planners to schedule resources to personnel and 2d space within facilities, and then catch errors immediately as they occur (non-arrivals, resource scanned in incorrect area/by wrong personnel, etc.) The scheduling algorithms will allow planners to use available spaces more optimally (e.g. less frequently used resources stored farther back in dwell areas.) The tool will also employ Bayesian technologies to probabilistically infer the whereabouts of missing resources (even tools without id tags; e.g., drill bits) based on patterns discovered in their usage and location history. AreaAdvisor will have an intuitive, visual interface that allows users to edit schedules and layout resources within critical areas interactively with mouse or pen-tablet devices.