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This paper presents a novel methodology for the analysis of the data at Birmingham Airport to provide effective and useful information about the dwell-time that passengers have between different points of their visit to the Airport. Birmingham Airport has sensors that anonymously count the number of people passing through crucial access routes, including boarding gates and security points. These sensors provide an enormous amount of crude data which contains valuable information reflecting the time people spend on different parts of the premises, but extracting this information requires a complex processing of the data. The methodology presented in this work uses a genetic paradigm which is able to process that data using a compact and robust simulation model, so that the time spent by the visitors to the airport can be extracted from the raw data produced by the sensors.