Enhancing Environmental Surveillance Against Organised Crime with Radial Basis Neural Networks

A huge amount of data concerning the position of individual is often gathered in surveillance scenarios, to prevent crimes or to collect evidence of unlawful behaviour. Given the abundance of data available, detectives need advanced analysis means in order to set apart the interesting locations. This paper proposes a solution that makes use of radial basis neural networks to find the points of interests, i.e. Locations that have been used for meeting, for surveilled people whose paths have been traced. In our solution newly gathered data will be analysed in order to find points of interest, and will also be given to our neural network for further training. Our results show that the proposed approach is accurate enough and can improve the unaided search for meeting points between observed individuals.