David Anthony
University of Nebraska–Lincoln
14 Papers
128 Citations
David Anthony is an academic researcher from University of Nebraska–Lincoln. The author has contributed to research in topics: Wireless sensor network & Electrical conductor. The author has an hindex of 7, co-authored 14 publications.
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Papers
Sensing through the continent: towards monitoring migratory birds using cellular sensor networks
David Anthony,William P. Bennett,Mehmet C. Vuran,Matthew B. Dwyer,Sebastian Elbaum,Anne E. Lacy,Mike Engels,Walter Wehtje +7 more
- 16 Apr 2012
TL;DR: The developed platform is designed to monitor Whooping Cranes, an endangered species that conducts an annual migration of 4,000 km between southern Texas and north-central Canada, and leads to a new class of cellular sensor networks (CSNs) for time-critical and mobile sensing applications.
Environmental Reviews and Case Studies: Bringing Unmanned Aerial Systems Closer to the Environment
Carrick Detweiler,John-Paul Ore,David Anthony,Sebastian Elbaum,Amy J. Burgin,Aaron J. Lorenz +5 more
TL;DR: In this paper, UAVs have been used to collect environmental data, however, they are largely relegated to collecting data while other humans collect data, such as data collection and data analysis.
18
Patent
Antenna for wireless underground communication
Mehmet C. Vuran,Xin Dong,David Anthony +2 more
- 18 Jul 2013
TL;DR: In this paper, an underground antenna structure for radiating through a dissipative medium, the antenna structure includes a dielectric substrate, a feeding structure disposed on the substrate, and one or more electrical conductors.
Patent
Crop height estimation with unmanned aerial vehicles
Carrick Detweiler,David Anthony,Sebastian Elbaum +2 more
- 06 Sep 2016
TL;DR: In this paper, a UAV is configured to scan through a two-dimensional scan angle and is characterized by a maximum range, and a control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the drone and a top of crops in the agricultural field to within a programmed range of distances based on the maximum range of the scanner.
Surface classification for sensor deployment from UAV landings
David Anthony,Elizabeth Basha,Jared Ostdiek,John-Paul Ore,Carrick Detweiler +4 more
- 26 May 2015
TL;DR: This paper uses data from an onboard accelerometer measured during UAV landings to determine the softness of the ground, and examines a number of features from the accelerometer and four classification algorithms: LDA, QDA, SVM, and binary decision trees.