ArticleHardwareX2026
Design of a real-time energy monitoring system for profiling consumption in IoT nodes during local data processing.
Article in HardwareX, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
This work presents the development of a two-part platform designed to evaluate the energy performance of Internet of Things (IoT) devices. The first component is a real-time monitoring system capable of synchronously measuring voltage and current to estimate the energy consumption of IoT nodes during the execution of computationally intensive algorithms. The second component is a battery-powered IoT test node that includes a user interface for configuring the percentage of training data used in a linear regression algorithm (RedWine dataset). Experimental evaluation shows that the monitoring system provides stable and accurate electrical measurements, while the test node enables controlled variation of computational load. Results demonstrate a nearly linear relationship between energy consumption, processing time, and the proportion of training data, with evidence that reduced datasets can achieve comparable model accuracy at significantly lower energy cost. The proposed platform provides a practical tool for analyzing the trade-off between algorithmic performance and resource usage, supporting the design of more energy-efficient IoT systems.
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