IoT System Integrating Unmanned Aerial Vehicles and LoRa Technology: A Performance Evaluation Study

Abstract

Nowadays, the popularity of the unmanned aerial vehicles (UAVs) is high, and it is expected that, in the next years, the implementation of UAVs in day-to-day service will be even greater. These new implementations make use of novel technologies encompassed under the term Internet of Things (IoT). One example of these technologies is Long-Range (LoRa), classified as a Low-Power Wide-Area Network (LPWAN) with low-cost, low-power consumption, large coverage area, and the possibility of a high number of connected devices. One fundamental part of a proper UAV-based IoT service deployment is performance evaluation. However, there is no standardized methodology for assessing the performance in these scenarios. This article presents a case study of an integrated UAV-LoRa system employed for air-quality monitoring. Each UAV is equipped with a set of sensors to measure several indicators of air pollution. In addition, each UAV also incorporates an embedded LoRa node for communication purposes. Given that mobility is key when evaluating the performance of these types of systems, we study eight different mobility models, focusing on the effect that the number of UAVs and their flying speed have on system performance. Through extensive simulations, performance is evaluated via multiple quality dimensions, encompassing the whole process from data acquisition to user experience. Results show that our performance evaluation methodology allows a complete understanding of the operation, and for this specific case study, the mobility model with the best performance is Pathway because the LoRa nodes are distributed and move orderly throughout the coverage area.

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

“…Results show the robustness of SF12 towards the Doppler effect, while SF7, on the other hand, is proven to be sensitive to the drone speed, especially at a speed of 35 km/h and above. This measurement offered a new insight into the performance of LoRaWAN ® -based aerial communication because the previous study in [46] was limited to 50 km/h. Data from the EN were transmitted every 5 s, while data were received by the GW every 9 and 7 s for the case of SF12 and SF7, respectively.…”

“…From the table, it can be observed that the previous research works proved that LoRa is robust to Doppler shift, and five of these research works discovered that 80% of the packet is received under LoRa spreading factor 12 (SF12) via an experimental test on a moving car and human. Meanwhile, based on a simulation with a drone done by [ 46 ], drone speed at a maximum of 50 km/h does not affect the delay, jitter, packet loss, and output of LoRa. As the speed of VTOL drones is much faster than rotary-wing drones, there is a need to investigate the Doppler effects at a higher speed.…”

Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming

“…Unfortunately, the authors of [22] do not consider the use of LoRa for multiple flying UAVs communications-to let the farthest drones using nearby flying UAVs as relays broadcast their telemetry data to the LoRaWAN ground network-thus limiting the possible use cases and effective operational ranges of the system. Another UAV-to-ground LoRaWAN-based communication application has been proposed in [23], in which the use of multiple UAVs with on-board sensors for air quality monitoring applications is discussed, further providing additional system operational results. Even in this case, LoRa-based communications are still used for UAV-to-ground communications without exploiting the potential use of flying long-range communications for some specific scenarios.…”

Development and Implementation of a Hybrid Wireless Sensor Network of Low Power and Long Range for Urban Environments

“…Some algorithms have been proposed, such as the latency and coverage optimized data collection scheme for smart cities in [ 50 ], to improve the efficiency data collection using data mules, but in that case, LoRaWAN was ruled out because they did not want to depend on long-range wireless transmission issues. Other authors [ 51 , 52 ] are including Unmanned Aerial Vehicles (UAVs) in this type of network to extend coverage, simulating different mobility models to predict performance, and emphasizing the importance of Quality of Service (QoS). However, among the several available LPWAN technologies, there are limited works dealing with experimental results that may help in the configuration of new applications.…”