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. 2017 Feb 24;17(3):460.
doi: 10.3390/s17030460.

Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring

Carlos A Trasviña-Moreno  1 , Rubén Blasco  2 , Álvaro Marco  3 , Roberto Casas  4 , Armando Trasviña-Castro  5
Affiliations

Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring

Carlos A Trasviña-Moreno et al. Sensors (Basel). .

Abstract

Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

Keywords: LPWAN; LoRa; UAV; WSN; low power electronics; marine monitoring; remote sensing.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
System interaction amongst the different devices of the network. The straight-line arrow indicates the main data transmission flow, the dashed arrow represents the communications with the optional ground station and the others indicate the environmental input to the buoys.
Figure 2
Figure 2
Functionality of the hardware developed for the SIMMA project.
Figure 3
Figure 3
Design of the PCB for the environmental sensing buoys.
Figure 4
Figure 4
Block diagram of a sensor node’s peripheral connections.
Figure 5
Figure 5
Sensor node’s task diagram.
Figure 6
Figure 6
Control node: BeagleBone Black and IoT cape.
Figure 7
Figure 7
Control node software architecture.
Figure 8
Figure 8
Control node’s task diagrams.
Figure 9
Figure 9
Davis drifter buoy design. Modified from http://www.ims.uaf.edu/NPRBdrifters.
Figure 10
Figure 10
Upper part of the buoy where the electronics are housed and the external sensors are fixed.
Figure 11
Figure 11
Delta Wing UAV used in the SIMMA project.
Figure 12
Figure 12
Graphical user interface screenshot.
Figure 13
Figure 13
Initial flight test. To the left the sensor buoy placed on the ground and to the right the UAV with the master node mounted inside.
Figure 14
Figure 14
Drifting Davis buoy placed in El Tecolote (Mexico) beach for environmental data collecting.
Figure 15
Figure 15
UAV flight path for the trials at El Tecolote beach. The furthest waypoint was set at 8.62 km away from the launch area and the UAV flew at a maximum height of 30 m.
Figure 16
Figure 16
Data extracted by the master node from one of the buoys.
Figure 17
Figure 17
Water damaged sensor node.
See this image and copyright information in PMC

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