We’re proud to share that a new paper supported by the MISO project has been published at the ๐๐๐๐ ๐๐๐๐๐ ๐๐๐๐ ๐๐ง๐ฌ๐ญ๐ซ๐ฎ๐ฆ๐๐ง๐ญ๐๐ญ๐ข๐จ๐ง ๐๐ง๐ ๐๐๐๐ฌ๐ฎ๐ซ๐๐ฆ๐๐ง๐ญ ๐๐จ๐ง๐๐๐ซ๐๐ง๐๐!
๐ Title: ๐ด๐๐๐ข๐๐๐ก๐ ๐๐๐๐ ๐ข๐๐๐๐๐๐ก๐ ๐๐ ๐๐๐กโ๐๐๐ ๐๐๐ ๐ถ๐๐๐๐๐ ๐ท๐๐๐ฅ๐๐๐ ๐๐๐ ๐ด๐๐๐ก๐๐ ๐๐๐ ๐๐๐ก๐๐๐๐ ๐ถ๐๐๐๐๐ก๐๐๐๐ ๐ข๐ ๐๐๐ ๐๐ท๐ผ๐
๐๐๐โ๐๐๐๐๐๐ฆ ๐๐๐ ๐ด๐ผ-๐๐๐ ๐๐ ๐ถ๐๐๐๐๐๐๐ก๐๐๐
This publication presents an innovative framework that leverages AI and machine learning to calibrate NDIR sensors, significantly improving the accuracy of ambient greenhouse gas monitoring in challenging environments such as the Arctic and wetlands.
๐ Congratulations to the authors: Huy Duong Gia, Amir H. Taherkordi, Phuong Ha, Benoit Wastine, Bakhram Gaynullin, Federico Dallo, and Tuan-Vu Cao for this important contribution to advancing environmental monitoring technologies.
This work is part of the ๐๐๐๐ project, funded by the European Union, and aligns with our mission to enhance in-situ observation platforms using cutting-edge innovations.

