This is the
MISO project
MISO develops an autonomous observation system for monitoring of emissions of CO2 and Methane, the two most important greenhouse gases. The system is modular and is suited for use in hard-to-reach areas such as the Arctic or wetlands. It combines three observing platforms (a static tower-Gas ambient monitor , a static gas flux chamber and a UAV-based observatory using NDIR sensing technologies ) with a cloud platform. The system can be operated remotely , with minimum on-site intervention.
The MISO team has expanded existing technologies: we have improved detection limit and accuracy of an NDIR GHG sensor integrated in the platforms. The static platforms and the drone base are powered by a unique geothermal device. The communication between the three observing platforms and a data cloud uses a combination of Peer2Peer, G4/G5/LTE, LORAWAN and wifi technologies.
To ensure consistent measurements, the observing platforms are optimized for energy efficient autonomous operation. This includes on-platform detection of faults through an optimized Machine Learning calibration. The cloud platform stores model updates and fault detection information together with the raw measurements.
The system is co-developed with stakeholders from academia, monitoring and measurement systems, industry and policy. It is thoroughly documented and has been demonstrated in the Arctic and in Wetland .
NEWS
โ๏ธ๐ MISO Svalbard โ Energy-Efficient Gas Ambient Monitor
During the Svalbard field campaign, the MISO team tested an energy-efficient gas ambient monitor designed for long-term operation in harsh Arctic conditions. ๐ง ๐๐ข๐ง๐ฒ๐๐ ๐๐ง-๐๐๐ฏ๐ข๐๐ ๐๐๐ฅ๐ข๐๐ซ๐๐ญ๐ข๐จ๐งUsing TinyML, the device runs a calibration model directly on the sensor node. Together with the K96 gas sensor, this enables accurate, real-time greenhouse gas
โ๏ธ๐ MISO Svalbard โ End-to-End Data Transmission Test
During the Svalbard field campaign, the MISO team carried out additional communication tests to support autonomous GHG monitoring in Arctic conditions. โ ๐๐๐ก๐ข๐๐ฏ๐๐ฆ๐๐ง๐ญ๐ฌ โ ๏ธ ๐๐๐ฌ๐ฌ๐จ๐ง๐ฌ ๐๐๐๐ซ๐ง๐๐ Thanks to Huy Duong Gia, Torbjรธrn, Vishall, Jurian, and Thibault for their work during these tests. ๐ธ More insights from the Svalbard campaign coming
๐โ๏ธ MISO Svalbard โ Environmental Intelligence Test
As part of the Svalbard field campaign, we tested and validated our live update framework and communication setup for autonomous, intelligent sensors operating in Arctic conditions. ๐ง ๐๐ข๐ฏ๐ ๐๐๐ฎ๐ซ๐๐ฅ ๐๐๐ญ๐ฐ๐จ๐ซ๐ค ๐๐ฉ๐๐๐ญ๐A key goal was to verify that our low-power STM32-based sensor device could receive, authenticate, and install updated neural-network weights
Contact Info
Dr. Tuan-Vu Cao, project coordinator.
The Climate and Environmental Research Institute NILU.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under Grant Agreement No. 101086541.