The objective of this project is to demonstrate and validate the effectiveness of Data Mule (Mobile Ubiquitous LAN Extension) unmanned aircraft systems (UAS) at remotely downloading data from camera traps on Department of Defense (DoD) installations and determining cost-effectiveness compared with conventional ground based methods (i.e., access by vehicle and by foot). Demonstrations on DoD installations are especially important because of the unique access restrictions due to military uses and training, which can lead to lost opportunities to collect important biological data and data loss when equipment maintenance is not done in a timely manner. Data mule UAS will allow natural resource personnel to be more versatile and effective in collecting and retrieving essential remote biological data.

This project will explore the demonstration and use of a fixed-wing Ready Made RC Anaconda airframe that functions as a Data Mule by wirelessly transferring data from a ground-based camera trap to its onboard data storage device. The Data Mule system consists of a UAS and ground based camera traps, both equipped with compatible, wireless communication hardware and software which is designed to work across multiple UAS platforms. The Data Mule UAS uses ArduPilot, the gold standard among open-source autopilots, which has been thoroughly field tested using multiple UAS. The Data Mule UAS and camera traps are equipped with single board computers running an embedded version of LINUX that communicate using two wireless protocols. This two layer wireless communication system allows for fast data transmission along with effective power management for system longevity. The Data Mule UAS works by creating a low-cost (i.e., financial and energy requirements) wireless communication link from the Data Mule UAS to the ground-based system attached to the camera traps. The Data Mule UAS flies autonomously on a pre-determined path to the camera traps and circles them at an altitude of 50-120 m (164.0-393.7 ft), while downloading the photos. The flight path can change dynamically in response to changes in battery level and environmental conditions. When the Data Mule UAS is returned to the ground or the office, data can be transferred from the Data Mule UAS onboard data storage device to a computer. The Data Mule UAS also has a built in safeguard against data loss; data on the ground-based camera trap will not be deleted until a command is given through this wireless communication during the next flight, thus ensuring that data will not be lost in case something happens to the Data Mule UAS on the return flight. A successful demonstration of the Data Mule UAS technology will include criteria, such as: 1) consistent and reliable mission command and control (e.g., following predetermined flight paths); 2) reliable communication between UAS and camera trap data; 3) improved data acquisition compared with conventional ground-based methods; 4) improved cost effectiveness in data acquisition; and 5) greater access to field sites compared with ground-based methods.

This demonstration and validation project has broad applicability across all military branches/installations that manage natural resources or have an Integrated Natural Resource Management Plan (INRMP). Monitoring and reporting of such species is an important management concern at all DoD installations in order to ensure their continued ability to support training and testing missions. Researchers expect the use of the Data Mule UAS as a safer, more efficient, and more cost effective alternative for all DoD installations that use and access remote monitoring systems, such as camera traps, compared with conventional ground-based methods for manually downloading field data. The use of the Data Mule UAS technology will likely fund itself within a short period of time based on anticipated cost savings and efficiencies that this technology will provide DoD personnel on military installations. Long-term benefits of this technology include data collection continuity, greater overall monitoring efficiency, and less data loss. The technology is designed for scalability, so it can be implemented across DoD installations of a variety of sizes. The findings of the project can be widely applied to any remote natural resources monitoring, including at-risk species and TES (e.g., Sonoran pronghorn and light-footed clapper rail), across nearly all military installations and branches of the DoD and can help DoD natural resource managers and biologists retrieve data more effectively and efficiently.