Artificial intelligence is often associated with heavy computing demands and high energy consumption—obstacles that limit its use in the Internet of Things (IoT), where sensors and devices typically run on minimal power and processing capabilities. However, researchers from the E-MINDS project have developed methods to make AI efficient enough to run on extremely limited hardware, paving the way for smarter, low-power applications in industry and beyond.
A joint initiative involving the COMET K1 center Pro2Future, Graz University of Technology (TU Graz), and the University of St. Gallen, the E-MINDS project has demonstrated how specialized AI models can operate locally on devices with just 4 kilobytes of memory. These models are able to perform tasks such as identifying sources of interference in ultra-wideband (UWB) localization systems, without relying on cloud computing or external processors.
Continue reading… “E-MINDS Project Brings Efficient AI to Tiny IoT Devices”