부산대학교 도서관

Recent advances in Internet of Things (IoT) and Artificial Intelligence (AI) technologies help ecosystem monitoring to shift towards automated monitoring with low power sensors and embedded vision on powerful processing units. Vision-based monitoring devices need an effective power management and control system (PMCS) with system-adapted power input and output capabilities to achieve power-efficient and self-sustainable operation. Here, we present a universal power management solution for automated ecosystem monitoring devices, compatible with commonly used off-the-shelf edge processing units (EPUs). The proposed design is specifically adapted for battery-powered EPU systems by incorporating power-matched energy harvesting (EH), a power switch with low-power sleep mode, and simple system integration in an MCU-less architecture with automated operation. We use a 4-month environmental case study to monitor plant growth under 4mg microplastic (MP) exposure, demonstrating that the setup achieved continuous and sustainable operation. In this plant phenology case study, our power management module is deployed in an embedded vision camera equipped with a 5W solar panel and five various environmental sensors. This work shows the usability of the power management board in environmentally relevant use cases and for tasks in agricultural applications.