Energy-Efficient Aerial Data Aggregation for IoT: From Prototyping to Large-Scale Implementation

Abstract

The integration of unmanned aerial vehicles (UAVs) within the Internet of Things (IoT) framework has emerged as a compelling solution to address the energy constraints that impede the full realization of IoT potential. As IoT applications continue to proliferate across industries, the dependence on battery-powered devices poses challenges in terms of longevity, maintenance, and sustainability. UAVs have been widely promoted as efficient enablers for aerial data aggregation in IoT networks due to their high capability of approaching hard-to-reach areas. Recently, UAVs have been integrated with the wake-up radio (WuR) technology to further extend the lifetime of IoT networks. In this article, we explore the theoretical foundations, technical intricacies, and practical implications of the integration of UAVs and WuR technology, showcasing its capability to extend network coverage, prolong operational lifespans, and enhance data reliability. More specifically, this work proposes a comprehensive design and implementation of a UAV-enabled WuR and data collection (U-WuRIoT) system, with a focus on achieving extended wake-up range and low power consumption. Based on the obtained measurements, we compare the U-WuRIoT system against the traditional duty-cycling (DCY) scheme. The results highlight the efficiency of U-WuRIoT in overcoming the trade-off between energy consumption and data-collection reliability. Furthermore, we go beyond prototyping to test U-WuRIoT in large-scale deployments by developing a comprehensive analytical framework using stochastic geometry. Drawing insights from both analytical constructs and experimental validation, this work envisions a future where UAV-WuR synergy unleashes the full potential of IoT applications while surmounting the challenges of energy constraints.

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