How AI and IoT are helping scientists overcome climate model challenges

#Researchers use artificial intelligence and IoT technology to remotely monitor moss growth in the harsh environment of Antarctica. Through LoRaWAN remote transmission and AIoT, the system can collect key data such as temperature and humidity without excessive data processing. This breakthrough demonstrates the potential of combining artificial intelligence and the Internet of Things to improve microclimate models and aid climate change research. What challenges do climate models pose, what do researchers do, and how does this demonstrate the power of artificial intelligence and the Internet of Things?

What challenges do climate models pose?

In the field of climate science , creating accurate climate models and identifying evidence supporting climate change theories poses many challenges to scientists. Although there is overwhelming evidence that global temperatures and carbon dioxide levels have continued to rise since the Industrial Revolution, it is difficult to prepare for the creation of oceans due to the extreme complexity of Earth's climate and the incredibly complex interactions between different environmental factors. Model linking planes, atmospheric composition, and global carbon dioxide emissions.

For example, rising carbon dioxide increases temperatures, but historically temperatures have risen before carbon dioxide levels rise. So it's understandable to think that carbon dioxide won't cause temperatures to rise. However, a closer look reveals that rising carbon dioxide levels cause global temperatures to rise. The reason carbon dioxide lags behind temperature rises is because of a positive feedback effect, in which a slight increase in temperature causes the oceans to release more carbon dioxide, causing the temperature to rise. rise.

To create accurate climate models, researchers need as much data as possible, and that data needs to include everything from global temperatures to local air pollutants and wind speeds. However, accessing large amounts of data can also be a double-edged sword, as finding relevant patterns in the data can be difficult.

Finally, obtaining data from remote locations, such as the Arctic, requires sensors to be able to run for long periods of time, given that local internet access is often unavailable, and few people are able to actively monitor sensor installations. This is an incredible challenge.

Antarctic researchers use artificial intelligence and the Internet of Things to conduct climate monitoring of mosses

Recognizing the need for better climate monitoring in remote areas, a team of Antarctic researchers recently combined artificial intelligence and the Internet of Things Technologies have combined to create wireless devices capable of remotely monitoring moss. According to researchers, mosses are an "Antarctic forest" that play an important ecosystem role in sub-zero conditions.

Just as trees provide a rich ecosystem for wildlife, mosses provide support for small life forms including bacteria, tardigrades and fungi by helping to insulate the permafrost in ice-free areas of Antarctica. a prosperous ecosystem. At the same time, moss helps reduce carbon dioxide in the atmosphere, making it an important carbon dioxide sink. Therefore, monitoring the status of Antarctic moss can help researchers understand how climate change is affecting Antarctic biodiversity and the overall environment.

However, monitoring moss in socially distanced locations poses several challenges, including data collection, processing and transmission. Therefore, researchers turned to artificial intelligence and the Internet of Things for data processing, while utilizing LoRaWAN for remote transmission.

The low-bandwidth nature of LoRaWAN means that not all data collected from sensors can be transmitted, so localized artificial intelligence and edge computing allow monitoring devices to decide what should be sent. Dubbed Artificial Intelligence for the Internet of Things (AIoT), the system helps researchers create better microclimate models by enabling them to collect the most relevant data, including temperature, humidity and images, without having to process large amounts of data.

How does this prove the power of artificial intelligence and the Internet of Things?

Almost any IoT device can be designed to transmit large amounts of data in real time for processing by some remote server, although this has not been possible in the past Might be acceptable, but as more and more data is collected, it becomes impractical. Using artificial intelligence to preprocess data, determine relevant content and selectively send data will help improve not only future IoT services, but the Internet as a whole. This device model will also help encourage the installation of larger device networks, as existing internet infrastructure will be under less pressure.

For researchers, using artificial intelligence to filter out the most critical data can help create more accurate models. However, AI is only as good as the model it is trained on, which means that any mistakes or assumptions made by the AI ​​will affect the research models created from the data filtered and processed by the AI.

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