| Project Detail |
Eco-friendly breakthrough in IoT energy solutions
The rapid growth of the internet of Things (IoT) has led to unsustainable energy demands and a surge in electronic waste due to short-lived devices. To address these issues, the EIC-funded ELEGANCE project is pioneering a revolutionary approach to IoT edge computing. ELEGANCE aims to develop eco-friendly, printable, and light-operated processing technology, leveraging recyclable materials to achieve a zero environmental footprint. By integrating energy-efficient in-memory computing and visual sensing into a single component, ELEGANCE is set to create neuromorphic and AI systems optimised for wearable, healthcare, and other edge-computing applications. This breakthrough promises to reduce energy costs and environmental impact while meeting growing consumer demands.
Today’s Internet-of-Things (IoT) incorporates a complex distributed network of wireless sensors and processors connected to the cloud. These platforms and their data-processing needs are creating a stronger and stronger demand for energy that is not sustainable. At the same time, the increasing consumers demand for IoT electronic devices and their limited lifespan, are significantly contributing to the world’s fastest-growing waste stream, known as electronic waste. To avoid an unsustainable energy cost in this data deluge, disruptive innovations in electronics from material to systems are urgently required. ELEGANCE proposes the development of a radically new, printable and light-operated processing technology specialized for IoT edge-computing applications. The project implements an eco-sustainable approach at component and processes level, where abundant, recyclable eco-friendly materials are employed, targeting a zero environmental footprint strategy. The processor’s building block includes a hybrid stack of an oxide optoelectronic memristor with an electrochromic layer on top exhibiting a unique light-triggered Processing-in-Memory enabling simultaneous IoT energy-efficient computing and visual sensing. In-memory computing schemes, such as crossbar memristor arrays, will be implemented employing low-cost, industrially compatible sustainable printing techniques. This will enable the design of energy efficient neuromorphic and artificial intelligence computing systems optimized for a plethora of consumer applications in the wearable, healthcare, and edge-computing sectors, making ELEGANCE an ambitious and technologically concrete breakthrough for the IoT with high potential for large societal benefits. |
