Advanced Data Analytics Seminar: Are Supervised Learning Algorithims the Key to a Paradigm Shift in the Way We Measure Air Pollution?
Venue: The Dalton Room, UMIC, 48 Grafton Street, M13 9XX
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Speaker: Dr Pete Edwards (University of York)
The Data Science Institute invites you to the next Advanced Data Analytics Seminar taking place on 14th November 2017. Dr Pete Edwards from the University of York will present 'Are supervised learning algorithms the key to a paradigm shift in the way we measure air pollution?'.
Low cost chemical sensors may prove to be a disruptive technology for air pollution measurements. The potential for these technologies is huge, enabling measurements on previously unachievable spatial scales and providing affordable tools to help tackle one of the largest environmental health risks in the developing world. Recent academic scrutiny has highlighted several issues with the relatively simple analytical methods used in these sensors, compared with traditional monitoring equipment, and methods to overcome these challenges need to be developed before they can reach their full potential. One of the most significant of these challenges is the problem of multiple cross-interferences on sensor signals. Correcting for these interferences with supporting high quality observations or regular calibration rapidly offsets their low cost advantage. The application of supervised machine learning algorithms to the modelling of complex sensor responses has shown significant skill in extracting useful signals, and could be the key to unlocking the technologies full potential.
If you would like to attend please register your place using the link below. Light refreshments will be provided after the seminar.