Electronic devices including smartphones and laptops could soon be used to ‘see’ in the dark using bat-like echolocation, claim researchers in Scotland.
The scientists at Glasgow University used the speakers and microphone from a laptop to generate and receive acoustic waves in the kilohertz range, and also used an antenna to do the same with radio-frequency sounds in the gigahertz range, collecting the data as a single person moved through a room. They simultaneously recorded data about the room using a time-of-flight camera which measures the dimensions of the room and provides a low-resolution image.
Repeating this process hundreds of times, they used the combined sound and camera data to train an algorithm to associate specific delays in the echoes with images. Over time, the algorithm was able to generate its own images based on the echolocation data. The work is published in Physical Review Letters.
“Echolocation in animals is a remarkable ability, and science has managed to recreate the ability to generate three-dimensional images from reflected echoes in a number of different ways, like RADAR and LiDAR,” said co-lead author Dr Alex Turpin, from Glasgow’s School of Computing Science and School of Physics and Astronomy.
“What sets this research apart from other systems is that, firstly, it requires data from just a single input – the microphone or the antenna – to create three-dimensional images. Secondly, we believe that the algorithm we’ve developed could turn any device with either of those pieces of kit into an echolocation device.”
Turpin and co-author Dr Valentin Kapitany believe the technology could reduce the cost of 3D imaging and have cited potential applications for their echolocation platform.
“It’s clear that there is a lot of potential here for sensing the world in new ways, and we’re keen to continue exploring the possibilities of generating more high-resolution images in the future,” Turpin said in a statement.
“A building could be kept secure without traditional cameras by picking up the signals reflected from an intruder, for example. The same could be done to keep track of the movements of vulnerable patients in nursing homes. We could even see the system being used to track the rise and fall of a patient’s chest in healthcare settings, alerting staff to changes in their breathing.”