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A semi-autonomous field survey device

Description:

TECHNOLOGY AREA(S): Sensors 

OBJECTIVE: Develop a low-cost semi-autonomous mobile observation device that has the capability to collect data required to comply with the Endangered Species Act, the Sikes Act, and the Migratory Bird Treaty Act that would otherwise require “booths on the ground”. 

DESCRIPTION: Most wildlife monitoring efforts depend on pre-WWII vintage Radio Direction Finding (RDF). Generating a single position data point requires a human tracker to hike out and often involving a lengthy search with antenna held aloft, then to use a separate GPS device to discern the location on a separate electronic device (iPad or the like). This system is expensive, time consuming and prone to transcription errors. The radios have relatively short range when tracking is done with a ground level antenna and often the species in question moves out of range between tracking dates. These missing species must then be tracked at even greater expense. HAM radio operators have long had a system called Automatic Packet Reporting System (APRS) for tracking multiple objects in real time. APRS contains a number of packet types, including position/object/item and telemetry. The position/object/item packets contain the latitude and longitude, and a symbol to be displayed on the map, and have many optional fields for other digital information. Positions of fixed stations are configured in the APRS software. Moving stations (portable or mobile) automatically derive their position information from a GPS receiver connected to the APRS equipment. The multi-channel nature, real time transmission inherent in the system allows a great variety of information to be streamed. A low power transmitter on the mobile device transmits the information to a higher power digi-peater (digital repeater) for linkage to a so-called internet gate (I-gate) for transmission to the web. The position of all subjects can be displayed on a screen in real time and recorded continuously for future analysis. In autonomous mode the device could be set to search a grid (similar to a Roomba vacuum cleaner) and identify features of interest (e.g. desert tortoise burrow openings). The device would be able to change direction upon encountering obstacles, to detect features by comparing reference photos to features encountered, and to sense steep drops to keep it from falling off cliffs. Once a feature has been tentatively identified the camera could be remotely accessed by a biologist to confirm the feature or reject it. If confirmed a GPS location would be recorded for follow-up as needed. In man-active mode the device would be equipped with cameras (one for the driver and a pan and tilt camera for the observer) and a senor array for environmental parameters. The device would have the potential for remote observations by any number of observers and would be much less intrusive than a human. Man-active mode also has the potential to recorded observations of wildlife behavior yielding vital information for managers without the typical constraints: the cost of hiring and field workers, logistical problems, weather conditions inimical to high quality data gathering, and the corrupting effect of human presence on the behavior observed. The semi-autonomous field survey device would have a mobile observation platform that evokes no fear on the part of the wildlife being observation. This device has the potential to save hundreds of thousands of dollars and provide better data for compliance with applicable laws and regulations. For example in 2016 CEV has a project to survey Edwards AFB for desert tortoises that cost approximately 500 thousand dollars and it will collect only presents and absence data for one species. A semi-autonomous mobile observation device could collect data on all species present as well as a sensory array to collect environmental parameter data. As envision the telemetry package would achieve the following advances: 1)The ability for simultaneous real time tracking and display of an indefinite number of animals this would allow use of biologist’s time in an unprecedentedly well-targeted way; 2) Recording of detailed movement information a full-time record rather than infrequent single position points; 3) With the addition of a sensors package on the device the recording of time-linked environmental information from specific locations. This information would vastly enrich our knowledge of the wildlife for a modest investment in equipment. 

PHASE I: Research in this phase should focus on device stability in rough terrain to prevent device tip over, bandwidth constraints for operation of the vehicle and camera resolution, battery life/recharging- current batteries require fairly frequent recharging and the method of delivering electricity to the vehicle – i.e. prove of concept. 

PHASE II: Phase II should be focused on system design, manufacturing, environmental maintenance, and quantification of system performance of a pre-production prototype. 

PHASE III: Military Application: Military bases are required by the Sikes Act to manage the wildlife on their bases. Historically, this data has been collected by “booths on the ground” biologist. Field biologist are expensive and sometime difficult to find to provide the data need to comply with the various federal wildlife related laws (ESA, MBTA, Lacy Act, etc). Commercial Application: All federal and state agencies that manage land are required by various laws and regulations to manage the wildlife on their land. As on military land, this data has been historically collected by “booths on the ground” biologist. With reduce budgets and limited manpower these agencies must still comply with the various federal wildlife related laws. 

REFERENCES: 

1: Balanis, C.A., Antenna theory: analysis and design2012: John Wiley & Sons.

2: Burke, B.F. and F. Graham-Smith, An introduction to radio astronomy. 2010: Cambridge University Press.

3: Ian Wade, G3NRW, ed. (August 29, 2000). "APRS Protocol Reference"

4:  Keaveny, J.J., Analysis and Implementation of a Novel Single Channel Direction Finding Algorithm on a Software Radio Platform. 2005.

KEYWORDS: Low Cost, Semi-autonomous, Remotely Operated, Mobile Observation Devices, Flexible Environmental Factor Monitoring 

CONTACT(S): 

Danny C. Reinke (412 CEG/CEV) 

(661) 277-9133 

danny.reinke@us.af.mil 

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