In-Vehicle Big Data Exploration for Road Maintenance (Discussion Paper)

Big Data Exploration techniques may benefit from the availability of huge amount of data (e.g., collected from IoT infrastructures) for improving resilience of monitored systems. In this paper, we discuss the application of such techniques in a research project to pursue mobility resilience in Smart Cities applications. Among the aspects to be considered for enabling resilience in mobility, we specifically focus on road maintenance, gathering data streams from vehicles equipped with sensors and designing proper exploration scenarios. Scenarios rely on three precise components as main pillars of the proposed approach: (i) a multi-dimensional model apt to represent the road network and to enable data exploration; (ii) data summarisation techniques, in order to simplify exploration of high data volumes; (iii) a measure of relevance, aimed at attracting the attention of the road maintainers on relevant data only.