Tyrol's universities shape the future: AI to predict natural risk
Tyrol's universities shape the future: AI to predict natural risk
In beautiful Tyrol, an exciting project is currently being worked on that could revolutionize the prediction of natural events. The project called Digischutz brings several universities and an innovative start-up called GMD to develop a sensor network. The aim is to use artificial intelligence (AI) the risk of natural disasters such as muries and stone strokes.
"So far we have often reacted reactively to natural events by blocking streets after a degenerate from a degeneration or evacuating houses," says Manuel Ferdik, professor at the MCI, who heads the project. He emphasizes the need to better predict future stone strikes in order to initiate preventive measures in good time.
multidisciplinary approach
digischeutz is not just a single project, but a community approach that combines different disciplines to improve the technology to protect the Tyrolean population. According to Ferdik, it is important that science and private sector work together to develop a resilient early warning system.
An essential step is to record stone strokes. GMD has developed special sensors that are already installed on stone traps in several Tyrolean regions. These sensors not only measure the vibrations caused by stones, but also environmental data such as temperature and humidity. In the future, the sensors should also register the size of the stones that meet the network.
technological innovations
The further development of this technology provides for the University of Innsbruck, which designs tailor-made Lora antennas. This technology enables data transmission over long distances with low energy consumption. The measurement data is currently being transferred via the mobile phone network, which is not only energy -intensive, but also restricts the lifespan of the battery of the sensors.
"We are working on using the sensors' housing as an antenna and replacing the batteries with solar -powered solutions", Ferdik describes the future planning. In this way, the system could become almost independent of external energy and function optimally in the rough Tyrolean nature.
From the beginning of 2025, the data collected should be used to train an artificial intelligence that recognizes patterns in the natural events. Ferdik explains that the AI should learn to relate various factors such as temperature and humidity and to evaluate the risk of stone strokes based on this.
"The more data we collect, the better the AI can learn where and when stone strikes occur," he explains. This is a significant step to achieve the long -term goal of digesture protection, which also consists in interaction with further data records from weather observations, room information systems and straw observation programs.
The researchers should be able to train the AI not only on stone strikes, but also on other natural events such as muries or floods, this could lead to more comprehensive prediction options. Ferdik is convinced that such a proactive approach is particularly important in view of the increasing weather extremes due to climate change.Information on this innovative project can be found in a detailed report on www.top.top.top.top.top.top.top.top.top.top.
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