Safe Ways: Early warning system for earthquakes in Istanbul
A metropolis of 13 million inhabitants, Istanbul is arming itself for a major earthquake. When it comes, nobody to this day can predict. So researchers are working on an early warning system. “This could make it possible to take emergency measures in good time, for instance shutting off electricity, lowering the pressure in gas lines, and deploying rescue services to areas that are expected to be hit particularly hard”, explained Joachim Fischer. The professor of computer sciences at the Berlin Humboldt University runs METRIK , a special postgraduate programme where scientists from various institutions can develop e.g. technologies serving as the basis for such an early warning system.
The idea: The city is covered with a network of thousands of autonomous sensor nodes. No bigger than a milk carton these nodes house a CPU, an aerial and sensors that register vibrations, measure their propagation, and transmit the data from node to node, e.g. via WLAN, to a central site. Since 2008, a small trial network of twenty nodes has been operating in Istanbul. The most important task for the computer scientists is to teach these initially autonomous nodes to cooperate. Only when they can do so will the teams of neighbouring nodes be able not only to measure local vibrations, but also to analyse them immediately and so determine the direction and speed of their propagation. These collated data must then be able to find the optimal route to the safety centre. For this purpose, the system should also be able to identify potential malfunctions like defect nodes, overloaded paths or routes disrupted by the weather. In addition, special “gateway nodes” are linked via the internet to existing geoinformation systems (GISs) that enable rescue services to analyse disaster data specific to the affected area with great precision.
At present the METRIK researchers are setting up the wireless “Humboldt Network” on Adlershof roofs. This is a test network of a hundred nodes that will go into operation at the official launch of the second funding round in May of this year. With simulated data from seismic waves, they intend to test and optimise the response and functions of the network on site. “Yet our work goes further: The principles we are developing can also be used for a great many other applications, with far greater visionary potential,” emphasised Fischer. For instance, networks of temperature sensors can help to detect forest fires or analyse the relationships between high temperatures and patient mortality at hospitals.
Silvia Nitz of GFaI, the Society for the Promotion of Applied Computer Science, is convinced that computer science can provide key safety services. She runs a subsection of SinoVE, a project for safety in open transportation systems funded by the Federal Ministry for Research and Technology and finding key support from Deutsche Bahn, Siemens and Bosch. Taking Frankfurt main railway station as its example, this project is intended to demonstrate how streams of people can be safely directed in danger situations. In order to supplement existing monitoring systems like video surveillance, the researchers intend to simulate streams of people, for instance when thousands of football fans enter the railway station.
“One key basis for this is a 3D model of the railway station,” explained Nitz. “For most buildings, though, there are only the usual 2D CAD plans available, showing lines open to interpretation.” Nitz and her colleagues are developing a software method that, like an experienced architect, can transform these drawings into a 3D model – automatically. “It is especially important to recognise how rooms are interconnected, or the types of doors that could cause bottlenecks for large crowds,” explained Nitz. On this basis, GFaI methods can automatically generate maps of escape routes that dynamic models can then adjust immediately to danger situations.
by Uta Deffke