Abstract
Rural IoT sensor networks, prevalent in environmental monitoring and precision agriculture, commonly operate over some variant of the IEEE 802.15.4 standard. Data collection from these networks is often challenging, as they may be deployed in remote regions where existing backhaul infrastructure is expensive or absent. With the commercial and industrial success of Unmanned Aircraft Systems (UAS), there is understandable interest in using UASs for delay tolerant data collection from 802.15.4 IoT sensor networks. In this study, we investigate how to optimize 802.15.4 networks for aerial data collection, which, unlike other wireless standards, has not received rigorous evaluation for three-dimensional aerial communication. We analyze experimental measurements from an outdoor aerial testbed, examining how factors, such as antenna orientation, altitude, antenna placement, and obstruction, affect signal strength and packet reception rate. In our analysis, we model and predict the quality of service for aerial data collection, based on these network configuration variables, and contrast that with the Received Signal Strength Indication (RSSI)—a commonly used signal strength metric. We find that network configuration plays a significant role in network quality, which RSSI, a mediator variable, struggles to account for in the presence of high packet loss. We conclude with a discussion of strategies for optimizing sensor network configuration for aerial data collection, in light of our results.
Highlights
Unmanned Aircraft Systems (UAS) are a promising technology for data collection from outdoor sensor networks
Our work provides three key contributions: (1) We conduct performance measurements of the Received Signal Strength Indication (RSSI) and Packet Reception Rate (PRR) by evaluating the impact of variables, such as altitude, displacement, antenna orientation, obstruction, transmission rate, and transmitter elevation
(2) We use the results to model the independent impact that each variable has on RSSI and PRR. (3) We show how network configuration can be used to model and predict network performance
Summary
Unmanned Aircraft Systems (UAS) are a promising technology for data collection from outdoor sensor networks. Environmental and agricultural applications may not have access to existing Internet backhauls for data delivery because low population densities in rural areas are unlikely to provide economic incentive for cellular providers to serve these remote areas. As these types of applications may be in difficult or inaccessible terrain that span large geographic areas, manual “sneaker-net” data collection can be dangerous and labor intensive [1]. UASs are deployed as aerial network relay nodes [2,3,4,5] or as data mules [6,7]. UASs can likewise supplement existing communication infrastructure, in vehicular networks [11] for example, as well as rural applications in environmental monitoring [12,13] and precision agriculture [14,15]
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