Emergency responders such as firemen, policemen and disaster rescue workers could soon use a powerful new tool to locate one another as well as survivors during missions.
Prof Tan Soon Yim at Centre for Infocomm Technology (INFINITUS), School of Electrical and Electronic Engineering, has come up with a Real-Time Localisation (RTL) system that drastically reduces the amount of hardware needed and works even in environments filled with typical signal-blocking obstacles. Their revolutionary technology could be used in rescue and counter-terrorism missions, and in places without Global Positioning System (GPS) signals, such as tunnels.
Two localisation techniques are often used in cities and buildings. One method uses reference nodes installed at known locations to pinpoint mobile nodes carried by people or objects. This system, however, usually requires at least three reference nodes to have line of sight to the mobile node, so many reference nodes must be installed. The other technique, called “fingerprinting”, does not need sightlines between the reference and mobile nodes, but users must have prior knowledge of the characteristics of the signals passing between the nodes. They must also calibrate the data for different environments.
Both techniques are impractical for emergency missions, such as riot control and search-and-rescue situations, as the environments are usually unknown to the responders and pre-installing reference nodes is not feasible. The School system consists of mobile nodes that use antenna array to send and receive microwave signals even through obstacles such as walls. Each node has four commercial, off-the-shelf Wi-FI antennas, making any two nodes a multiple input and multiple output localisation system.
In buildings, just one node is needed as the reference, compared to existing techniques that use at least five times as many reference nodes. Emergency responders can also use the mobile nodes to track one another. The system pinpoints locations within 1m accuracy.
With some configuration, the system can also locate unknown wireless signal emitters within 1m accuracy, to find, say, trapped victims or terrorists using remote detonation devices. Professor Tan Soon Yim added: “Our technology is especially useful in GPS-denied environments, for vehicle tracking and in malls to enhance the shopping experience.”
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