A scalable data-driven architecture for real-time multidisciplinary volcano monitoring

Abstract Nowadays, in the field of volcanic monitoring, as the number of monitoring stations, the related measured parameters and the complexity of the analyses performed on them increase, the traditionally used software architectures may prove inadequate. In this work we present a novel architecture to perform complex real-time analysis of multi-disciplinary data for volcanoes monitoring. The architecture is based on the idea of a set of independent workers exchanging messages on a distributed high performance message system. Workers are properly orchestrated in order to provide high throughputs and low latency times. A first platform implementing the architecture is presented with a real use case on Stromboli volcano monitoring where the Neolo system has been developed, and is described. Along this, it is described the adoption of the new platform also on the INGV-OV Surveillance Room. Used technologies and some workers that have been developed are also presented.