As fireball networks grow, the number of events observed becomes unfeasible to manage by manual efforts. Reducing and analysing big data requires automated data pipelines. Triangulation of a fireball trajectory can swiftly provide information on positions and, with timing information, velocities. However, extending this pipeline to determine the terminal mass estimate of a meteoroid is a complex next step. Established methods typically require assumptions to be made of the physical meteoroid characteristics (such as shape and bulk density). To determine which meteoroids may have survived entry there are empirical criteria that use a fireballs final height and velocity - low and slow final parameters are likely the best candidates. We review the more elegant approach of the dimensionless coefficient method. Two parameters, $alpha$ (ballistic coefficient) and $beta$ (mass-loss), can be calculated for any event with some degree of deceleration, given only velocity and height information. $alpha$ and $beta$ can be used to analytically describe a trajectory with the advantage that they are not mere fitting coefficients; they also represent the physical meteoroid properties. This approach can be applied to any fireball network as an initial identification of key events and determine on which to concentrate resources for more in depth analyses. We used a set of 278 events observed by the Desert Fireball Network to show how visualisation in an $alpha$ - $beta$ diagram can quickly identify which fireballs are likely meteorite candidates.
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