28 research outputs found
A noise robust automatic radiolocation animal tracking system
Agriculture is becoming increasingly reliant upon accurate data from sensor arrays, with localization an emerging application in the livestock industry. Ground-based time difference of arrival (TDoA) radio location methods have the advantage of being lightweight and exhibit higher energy efficiency than methods reliant upon Global Navigation Satellite Systems (GNSS). Such methods can employ small primary battery cells, rather than rechargeable cells, and still deliver a multi-year deployment. In this paper, we present a novel deep learning algorithm adapted from a one-dimensional U-Net implementing a convolutional neural network (CNN) model, originally developed for the task of semantic segmentation. The presented model (ResUnet-1d) both converts TDoA sequences directly to positions and reduces positional errors introduced by sources such as multipathing. We have evaluated the model using simulated animal movements in the form of TDoA position sequences in combination with real-world distributions of TDoA error. These animal tracks were simulated at various step intervals to mimic potential TDoA transmission intervals. We compare ResUnet-1d to a Kalman filter to evaluate the performance of our algorithm to a more traditional noise reduction approach. On average, for simulated tracks having added noise with a standard deviation of 50 m, the described approach was able to reduce localization error by between 66.3% and 73.6%. The Kalman filter only achieved a reduction of between 8.0% and 22.5%. For a scenario with larger added noise having a standard deviation of 100 m, the described approach was able to reduce average localization error by between 76.2% and 81.9%. The Kalman filter only achieved a reduction of between 31.0% and 39.1%. Results indicate that this novel 1D CNN U-Net like encoder/decoder for TDoA location error correction outperforms the Kalman filter. It is able to reduce average localization errors to between 16 and 34 m across all simulated experimental treatments while the uncorrected average TDoA error ranged from 55 to 188 m
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Federal Register
Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii
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Federal Register
Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii
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Federal Register
Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii
Social work with airports passengers
Social work at the airport is in to offer to passengers social services. The main
methodological position is that people are under stress, which characterized by a
particular set of characteristics in appearance and behavior. In such circumstances
passenger attracts in his actions some attention. Only person whom he trusts can help him
with the documents or psychologically
The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation
This Synthetic Aperture Radar (SAR) handbook of applied methods for forest monitoring and biomass estimation has been developed by SERVIR in collaboration with SilvaCarbon to address pressing needs in the development of operational forest monitoring services. Despite the existence of SAR technology with all-weather capability for over 30 years, the applied use of this technology for operational purposes has proven difficult. This handbook seeks to provide understandable, easy-to-assimilate technical material to remote sensing specialists that may not have expertise on SAR but are interested in leveraging SAR technology in the forestry sector
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Federal Register
Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii
Recommended from our members
Federal Register
Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii
Recommended from our members
Federal Register
Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii
A scoping study to assess the precision of an automated radiolocation animal tracking system
The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (5 ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28 days. The 12 tags recorded 36,452 transmissions with a mean transmission per tag of 3037. Each transmission included the tag number, date and time and the calculated longitude and latitude. The mean location and then the Euclidean distance from the mean location for each tag were calculated in order to derive location precision per tag. The overall precision for the 12 tags was ±22 m with a SD of 49 m with the most and least precise tags having precisions of ±8 m and ±51 m, respectively. As with other geolocation technologies, it would appear that structures in the environment cause signal propagation effects including multipath and non-line-of-sight, which result in errors in the derived locations. The distance from the mean data was log transformed (log10) and summarised in order to present all data over a 24-h period. There was a statistically significant decrease in precision between 11:00 and 17:00 h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24 h, with temperature, humidity, wind speed and pressure all having significant correlations with the precision data. The variance between individual tag transmissions were compared to see whether the distance between derived locations increased as time between transmissions increased. The means for each tag showed the same variance as the mean precision values, that is the more precise tags had lower means and the less precise tags had higher means. However, no tags showed a trend towards an increase in the distance between locations as the time between transmissions increased. In order to assess whether there was any spatial variability in the derived locations, the variability in distance between tags was compared for all tag combinations. Tags that were proximal to each other had shorter distances between the mean derived locations and less variance, whereas tags farther apart had large distances and large variance in the mean derived locations. The ARATS assessed in this static evaluation showed a lower level of spatial precision than commercially available global positioning systems. However the system could still have application when used to derive proximal associations between animals in low stocking-rate, extensive grazing situations such as are present in northern Australia