The European Union's BIOMACHINELEARNING project has created a neuromorphic network for odor recognition, running on neuromorphic hardware, which can receive real-time input from electrical gas sensors.
The project's researchers say the technology could lead to the development of a cost-effective, portable, and fully functional robotic nose.
When studying how to improve the accuracy and speed of odor detection and identification, the researchers found they could use bio-inspired signal processing to enhance the signals from sensors and resolve variations in gas concentrations resulting from of a phenomenon called "turbulence." Rapid concentration changes associated with turbulence can be resolved with inexpensive, off-the-shelf gas sensors and appropriate signal processing, according to the researchers.
"The signal-processing method we devised operates pretty much like an adapting neuron," notes principal researcher Michael Schmuker.
Neurons exchange information via short pulses of activity called "spikes," and the researchers are using specialized neuromorphic hardware to accelerate spiking computation and model brain circuits while maintaining computational efficiency. The input data is encoded by virtual olfactory receptors and then processed by a network based on an element of the insect olfactory system.
"With the right network, these systems have the potential to perform as well as conventional computers in pattern recognition, but at a fraction of the energy costs," Schmuker says.
From CORDIS News
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