RMIT University has developed a working prototype for a smart bionic eye that can see, remember, and interact with the world like the human brain, while using far less energy than today’s technologies.
By combining sensing, memory, and information processing, the neuromorphic vision device reduces the need to constantly move data between separate sensors, memory banks and processors.
RMIT has an international patent application filed under the Patent Cooperation Treaty (PCT) for the invention.
Building on Nature, Mimicking Vision
Led by Professor Sumeet Walia at RMIT’s Centre for Opto-electronic Materials and Sensors (COMAS), the system builds on breakthroughs involving super thin semiconductor materials that could underpin advanced robotics and low-energy AI systems.1,2
In lab tests, it can detect changes in what it sees, then store that information as memory and process it locally
“Nature has already solved many of the challenges we’re trying to address in electronics,” said Prof Walia.
“The human eye and brain work together incredibly efficiently, processing vast amounts of information using remarkably little energy. Our research is helping lay the foundations for technologies that work in a more similar way.”
The prototype is built on a series of advances using the atom-thin semiconductor molybdenum disulfide (MoS₂). The sensing, processing, and storage of information all takes place in a 2 cm by 2 cm chip, housed within a 15 cm by 14 cm by 3 cm prototype containing the electronics needed to read, process and communicate information.
Researchers have trained the system to recognise patterns including numbers, shapes and movement. In lab tests, it can detect changes in what it sees, then store that information as memory and process it locally.
Dr Taimur Ahmed, co-researcher and expert in neuromorphic vision devices at RMIT, said the result was a system that more closely mimics the way biological vision works.
“This is not just a sensor that captures information, it’s a sensor that can also process information,” said Dr Ahmed.
“Rather than constantly moving data between separate memory and processing units, much of that work happens much closer to where the information is generated.”
Figure 2. RMIT University’s neuromorphic vision prototype combines sensing, memory and processing within a single system, helping reduce the need to continuously transfer data between separate computing components. Credit: RMIT University.
Critical Challenges
A smart bionic eye would need to do more than simply capture images. It would need to identify important changes in a scene, store relevant information, and process visual signals rapidly while using very little energy.
The RMIT technology could address these challenges by allowing visual information to be filtered and interpreted at the point of sensing, reducing the amount of data that needs to be transmitted and processed elsewhere.
The team’s latest breakthrough also tackled another critical challenge: manufacturing.
They developed a cleaner, water-based fabrication process that transfers atom-thin semiconductors and electrodes with significantly fewer defects than conventional methods, producing devices with substantially improved electrical and light-sensing performance.
“Each breakthrough brings us closer to technologies such as a smart bionic eye,” said Prof Walia.
Figure 3. The neuromorphic sensor mounted on a circuit board used for testing and system integration. Credit: RMIT University.
A Vision For The Future
While practical applications remain years away, researchers believe the technology could also eventually support advanced machine vision systems, autonomous vehicles, robotics and intelligent sensors.
The work may also point towards a more sustainable future for artificial intelligence.
As AI drives demand for increasingly large and energy-intensive data centres, neuromorphic systems offer a different approach by processing information closer to where it is collected and reducing the amount of data that needs to be transmitted, stored and analysed.
“This work combines advanced materials, engineering, and artificial intelligence to address one of the defining challenges of our time: creating intelligent systems that are both powerful and sustainable,” said Prof Walia.
“If this RMIT technology can be scaled up, it could help reduce the amount of data that needs to be moved, stored and processed, making future AI systems more energy efficient.”
Companies interested to collaborate with the RMIT team should contact research.partnerships@rmit.edu.au.
References
Mao J, Abidi IH, Walia S, et al. PVA-mediated transfer of MoS2 and Au electrodes: A lithography-free route to ultraclean van der waals interfaces for high-performance electronics and optoelectronics. ACS Appl. Mater. Interfaces 2 September 2026; 18 (34): 46899–46909. doi: 10.1021/acsami.6c05536
Aung T, Giridhar SP, Walia S, et al. Photoactive monolayer MoS2 for spiking neural networks enabled machine vision applications. Adv. Mater. Technol. 2025, 10, 2401677. doi:10.1002/admt.202401677
