Researchers at The University of Osaka have developed a groundbreaking energy-efficient and high-precision measurement system leveraging the inherent similarity between waveforms generated by the same type of signal source. Unlike black-box approaches such as generative AI, the system is built on the explicit theoretical framework of compressed sensing. This innovative approach drastically reduces the amount of data required for accurate signal reproduction, leading to significant energy savings. Demonstrated with an electroencephalogram (EEG) measuring system, the technology achieved world-leading energy efficiency using only commercially available electronic components, consuming a mere 72μW. This breakthrough paves the way for long-term, battery-powered wearable devices and self-powered, battery-free IoT devices that can operate on minimal energy harvested from the environment, with broad applications in healthcare, disaster prevention, and environmental monitoring.

Scientists have created the first soft robots that can walk straight out of the machines that make them.

Researchers from Aarhus University have developed MARTINIS – a portable, low-cost, automatic lab that monitors soil chemistry in real time using planar optodes. The system can track oxygen and pH levels in situ without disturbing the soil. It enables detailed analysis of soil dynamics, supports climate research, and may inform sustainable farming practices. The open-source technology has been field-tested and is now being further developed for broader application.

A new study published in Frontiers of Engineering Management presents a systematic framework for optimizing cloud-integrated cyber-physical systems, addressing the complex interplay of reliability, performance, and power consumption. The research delivers actionable insights for cloud service providers to enhance operational resilience and sustainability in an increasingly data-driven world.