Time Allocation in Multi-UAV Energy Harvesting Network

Li, Yuchen; Zhou, Cong; Shi, Shuo; Xu, Zhenyu

doi:10.1007/978-3-030-90199-8_2

Cited by 1 publication

(1 citation statement)

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“…Tiurlikova et al [ 12 ] propose a UAV equipped with an inductive WPT link to charge LoRaWAN-enabled devices. Alternatively, Tiurlikova et al [ 13 ] present a multi-UAV energy harvesting network with multiple UAVs transmitting energy to several nodes through RF links.…”

Section: System and Iot Node Architecture And Related Workmentioning

confidence: 99%

UAV-Based Servicing of IoT Nodes: Assessment of Ecological Impact

Mulders

Cappelle

Goossens

et al. 2023

Sensors

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Internet of Things (IoT) nodes get deployed for a variety of applications and often need to operate on batteries. This restricts their autonomy and/or can have a major ecological impact. The core idea of this paper is to use a unmanned aerial vehicle (UAV) to provide energy to IoT nodes, and hence prolong their autonomy. In particular, the objective is to perform a comparison of the total energy consumption resulting from UAV-based recharging or battery replacement versus full provisioning at install time or remote RF-based wireless power transfer. To that end, an energy consumption model for a small license-free UAV is derived, and expressions for system efficiencies are formulated. An exploration of design and deployment parameters is performed. Our assessment shows that UAV-based servicing of IoT nodes is by far more beneficial in terms of energy efficiency when nodes at distances further than a few meters are serviced, with the gap increasing to orders of magnitude with the distance. Our numerical results also show that battery swapping from an energy perspective outperforms recharging in the field, as the latter increases hovering time and the energy consumption related to that considerably. The ecological aspects of the proposed methods are further evaluated, e.g., considering toxic materials and e-waste.

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Section: System and Iot Node Architecture And Related Workmentioning

confidence: 99%