​The barn owl locates its prey using a two-step method. First, it uses its sense of hearing to determine whether any rodents are within range. Only then does it "switch on" its sense of sight—a bigger energy consumer than hearing. Researchers at CEA-Leti found inspiration for their new energy efficient acoustic object location system in the owl's especially economical approach to hunting.

The researchers combined piezoelectric acoustic sensors with a local microprocessorless data processing system. A sensor emits ultrasound waves which, when they hit a target, generate two reflected waves which are in turn picked up by two other sensors—much like the owl's two ears. The tiny time lapse between when the two sensors pick up the waves and the distance between the sensors are used to determine the target's location. The computational model that underpins the system is inspired by the owl's cerebral cortex and is implemented in a near-sensor resistive memory.

The completely bio-inspired demonstrator was tested, and the results were encouraging. The system could use 100,000 times less energy than conventional systems with similar sensors and a microcontroller—without compromising on location accuracy. This kind of system could ultimately be combined with an image analysis system for use in robotics and, especially, drones.