Can AI predict natural hazards better?

How AI-IoT technology can make the Alpine region more resilient

The densely populated Alpine region is increasingly confronted with natural hazards that threaten both people and infrastructure. They are natural events that often occur quickly and without warning and can have enormous destructive power. The current MCI project “DigiSchutz” deals with the early detection of natural hazards with the help of artificial intelligence and the resulting options for action.

In order to better protect against natural hazards, it is necessary to recognize them at an early stage. To this end, endangered areas must be continuously monitored, early warning systems improved and the population sensitized. Sensor technologies can provide early information about an impending danger or trigger an alarm if a measured value is exceeded, so that suitable protective measures can be initiated immediately.

The “DigiSchutz” project, which is being implemented at the MCI in the research focus area 'Electronics & Data Analytics' in collaboration with the start-up GMD (Geomorphing Detection) from Innsbruck and the University of Innsbruck, shows how innovative technology and academic knowledge can be combined to overcome real challenges. It is about the development of an AI-based IoT solution for the early detection of natural hazards: the integration of sensor data and machine learning enables precise analysis and forecasting.

The project is being funded by the state of Tyrol as a lighthouse project for digitalization and is being implemented in the town of Kufstein, which is to be established as a model region for digitalization and natural hazard management. As the location for the pilot project, it is providing test environments and participating in the development of a digital safety net.

The aim of the project is to set up an early warning system for natural hazards based on artificial intelligence. In Kufstein, digital rockfall and mudflow warning systems are to be developed and a “Smart City Protective Network” established. The lighthouse project is intended to serve as a European showcase project for adaptation to climate change and will have far-reaching effects for Tyrol and beyond. The project results should contribute to the creation of new products and services in the field of geomonitoring.

The goal is to digitize protective structures against gravitational natural hazards, with a focus on the real-time monitoring of rockfall nets using intelligent sensors and gateways. Machine learning will be used to analyze the collected data and use it to predict natural hazards. The main challenges include the development of a functional sensor housing, the optimization of data transmission using LoRa (Long Range) technology and the implementation of machine learning models for event classification and prediction. LoRa makes it possible to manage a large number of sensors within a network and to process sensor data.

These challenges are to be overcome through intensive cooperation between the partner institutions and the use of state-of-the-art technologies. Thanks to the close cooperation between science, industry and public institutions, the “DigiSchutz” project is setting new standards in the field of natural hazard prevention. It shows how the use of AI and IoT technologies can increase safety and thus improve the population's quality of life.

GMD GmbH, a young start-up from Innsbruck, specializes in the development of intelligent IoT systems for predicting natural hazards and works closely with partners from the fields of geology, geotechnics and civil engineering as well as with the MCI and the University of Innsbruck. The MCI contributes its expertise in data science and machine learning, while the Institute of Mechatronics at the University of Innsbruck provides its expertise in the field of high-frequency technology and the development of LoRa modules and energy harvesting concepts. HTB Baugesellschaft mbH, with decades of experience in structural and civil engineering as well as special buildings in high alpine regions, is responsible for setting up test environments and assembling the measuring units.