Professor Sumeet Walia (left) and PhD researcher Aishani Mazumder. Picture courtesy RMIT University.
A neuromorphic invention, thousands of times thinner than a human hair, has been developed to ‘see’ and create memories.
Developed by researchers in Victoria, the tiny device is a promising step towards applications that can make rapid, complex decisions, such as in self-driving cars.
Enabled by the sensing element, doped indium oxide, this single chip requires no external parts to operate.
RMIT University engineers led the work, with contributions from researchers at Deakin University and the University of Melbourne.
The team’s research demonstrates a working device that captures, processes, and stores visual information. With precise engineering of the doped indium oxide, the device mimics a human eye’s ability to capture light, pre-package and transmit information like an optical nerve, and store and classify it in a memory system, similar to the way the human brain can.
Explaining further, first author and RMIT PhD researcher Aishani Mazumder said the human brain uses analogue processing, which allows it to process information quickly and efficiently using minimal energy.
“By contrast, digital processing is energy and carbon intensive, and inhibits rapid information gathering and processing,” she said.
“Neuromorphic vision systems are designed to use similar analogue processing to the human brain, which can greatly reduce the amount of energy needed to perform complex visual tasks compared with today’s technologies.”
By performing all necessary functions – sensing, creating, processing information, and retaining memories – without relying on external energy-intensive computation, team leader Professor Sumeet Walia said the new device was potentially capable of real-time decision making.
“Performing all of these functions on one small device had proven to be a big challenge until now,” said Prof Walia, from RMIT’s School of Engineering.
“We’ve made real-time decision making a possibility with our invention, because it doesn’t need to process large amounts of irrelevant data and it’s not being slowed down by data transfer to separate processors.”
The new device was also able to demonstrate an ability to retain information for longer periods of time, compared with previously reported devices, without the need for frequent electrical signals to refresh the memory. This ability significantly reduces energy consumption and enhances the device’s performance.
Potential Applications
The team used ultraviolet light as part of its experiments and is working to expand this technology even further for visible and infrared light – with many possible applications such as bionic vision, autonomous operations in dangerous environments, shelf-life assessments of food, and advanced forensics.
“Imagine a self-driving car that can see and recognise objects on the road in the same way that a human driver can, or being able to rapidly detect and track space junk. This would be possible with neuromorphic vision technology.”
Prof Walia said neuromorphic systems could adapt to new situations over time, becoming more efficient with more experience.
“Traditional computer vision systems, which cannot be miniaturised like neuromorphic technology, are typically programmed with specific rules and can’t adapt as easily,” he said.
“Neuromorphic robots have the potential to run autonomously for long periods in dangerous situations where workers are exposed to possible cave-ins, explosions, and toxic air.”
The human eye has a single retina that captures an entire image, which is then processed by the brain to identify objects, colours, and other visual features.
The team’s device mimics the retina’s capabilities by using single-element image sensors that capture, store, and process visual information on one platform, Prof Walia said.
“The human eye is exceptionally adept at responding to changes in the surrounding environment in a faster and much more efficient way than cameras and computers currently can,” he said.
“Taking inspiration from the eye, we have been working for several years on creating a camera that possesses similar abilities, through the process of neuromorphic engineering.”
Their findings and analysis are published in Advanced Functional Materials.1
Reference
1. Mazumder, A., Nguyen, C.K., Aung, T., et al., (2023), Long duration persistent photocurrent in 3 nm thin doped indium oxide for integrated light sensing and in-sensor neuromorphic computation. Adv. Funct. Mater. 2303641. doi.org/10.1002/.
