A Network of Monitoring Nodes to Analyze Dimensions of Volcanic Ash Samples

The investigation of volcanic ash particles granulometry is mandatory in order to cope with real needs of both urban and air traffic, as well as to manage its effect to human health. The approach presented in this paper relies on a computer vision-based methodology for the automatic detection of volcanic ash granulometry through a network of sensing nodes, providing high spatial resolution information, is proposed. The system architecture is presented, along with the proposed image processing methodology aimed to extract statistics on the collected sample of volcanic ash. The system characterization is also addressed. Results obtained in terms of repeatability, experimental variability and the system accuracy are given.

Automated summary

This paper proposes a computer vision-based method for the automatic detection of volcanic ash granulometry. The method utilizes a network of sensing nodes to provide high spatial resolution information, which can help to address the needs of urban and air traffic, as well as manage its impact on human health.