Abstract
The Internet of Things (IoT) nodes dedicated to off-grid usage must fully rely on their battery power for continuous operation. In that sense battery charging process design is one of the focal points for the complete system design. Nowadays, battery charging, for such devices, usually relies on solar power which is not, unfortunately, the source of constant energy. Both environmental and constructive elements could easily make a negative impact on the charging process and reduce the amount of collected energy. Furthermore, if the IoT nodes are in hazardous areas, they are less accessible, and the value of effective battery management is even higher. The requirements for the battery charging process implementation are considered as opposite – on one hand, the requirement is to run charging with the lowest possible frequency and not up to 100%, and on the other hand, the battery should always have enough energy to maintain regular operation. In this research, we present the structure of the custom-developed IoT node based on the ECS32 system-on-a-chip dedicated to operating in remote industrial areas, and with an accent of its battery charging routine. The current routine is based on a standard thresholds approach and improved by including consumption estimates for the predefined periods. This paper presents the first results and should pave the ground for further upgrades. In addition, the comparison with state-of-the-art charging approaches is presented, as the guidelines for future work.
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Acknowledgments
The Ministry of Education, Science, and Technological Development of the Republic of Serbia have funded this work, grant number 451-03-68/2022-14/ 200102. This work has been supported by the cost action CA 19135 CERCIRAS (Connecting Education and Research Communities for an Innovative Resource Aware Society).
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Rajković, P., Aleksić, D., Janković, D. (2024). The Implementation of Battery Charging Strategy for IoT Nodes. In: Zeinalipour, D., et al. Euro-Par 2023: Parallel Processing Workshops. Euro-Par 2023. Lecture Notes in Computer Science, vol 14352. Springer, Cham. https://doi.org/10.1007/978-3-031-48803-0_4
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DOI: https://doi.org/10.1007/978-3-031-48803-0_4
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