Bayesian Optimisation for Active Monitoring of Air Pollution

arXiv:2202.07595v2 Announce Type: replace
Abstract: Air pollution is one of the leading causes of mortality globally, resulting in millions of deaths each year. Efficient monitoring is important to measure exposure and enforce legal limits. New low-cost sensors can be deployed in greater numbers and in more varied locations, motivating the problem of efficient automated placement. Previous work suggests Bayesian optimisation is an appropriate method, but only considered a satellite data set, with data aggregated over all altitudes. It is ground-level …

abstract air pollution arxiv bayesian cost cs.lg legal locations low monitoring mortality numbers optimisation physics.ao-ph pollution sensors type