A scoping study to assess the precision of an automated radiolocation animal tracking system
•The mean spatial precision for the ARATS ear tags was ±22m.•Signal propagation effects and meteorological parameters affected spatial precision.•The time between transmissions showed no effect on the spatial precision. The spatial precision of a new automated radiolocation animal tracking system (A...
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| Veröffentlicht in: | Computers and electronics in agriculture 2016-06, Vol.124, p.175-183 |
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| creator | Menzies, Don Patison, Kym P. Fox, David R. Swain, Dave L. |
| description | •The mean spatial precision for the ARATS ear tags was ±22m.•Signal propagation effects and meteorological parameters affected spatial precision.•The time between transmissions showed no effect on the spatial precision.
The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (∼5ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28days. 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 ±22m with a SD of 49m with the most and least precise tags having precisions of ±8m and ±51m, 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 17:00h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24h, 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 com |
| doi_str_mv | 10.1016/j.compag.2016.04.001 |
| format | Article |
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The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (∼5ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28days. 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 ±22m with a SD of 49m with the most and least precise tags having precisions of ±8m and ±51m, 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 17:00h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24h, 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.</description><identifier>ISSN: 0168-1699</identifier><identifier>EISSN: 1872-7107</identifier><identifier>DOI: 10.1016/j.compag.2016.04.001</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Animals ; Automation ; Correlation ; Livestock ; Mathematical analysis ; Position (location) ; Precision ; Radiolocation ; Spatial ; Taggle ; Tags ; Temporal ; Tracking systems ; Variance</subject><ispartof>Computers and electronics in agriculture, 2016-06, Vol.124, p.175-183</ispartof><rights>2016 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c339t-e8f2a80e30165c5e01f41577c0291f626a336ce0a7a64f3ca549bb01314e88533</citedby><cites>FETCH-LOGICAL-c339t-e8f2a80e30165c5e01f41577c0291f626a336ce0a7a64f3ca549bb01314e88533</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.compag.2016.04.001$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27922,27923,45993</link.rule.ids></links><search><creatorcontrib>Menzies, Don</creatorcontrib><creatorcontrib>Patison, Kym P.</creatorcontrib><creatorcontrib>Fox, David R.</creatorcontrib><creatorcontrib>Swain, Dave L.</creatorcontrib><title>A scoping study to assess the precision of an automated radiolocation animal tracking system</title><title>Computers and electronics in agriculture</title><description>•The mean spatial precision for the ARATS ear tags was ±22m.•Signal propagation effects and meteorological parameters affected spatial precision.•The time between transmissions showed no effect on the spatial precision.
The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (∼5ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28days. 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 ±22m with a SD of 49m with the most and least precise tags having precisions of ±8m and ±51m, 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 17:00h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24h, 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.</description><subject>Animals</subject><subject>Automation</subject><subject>Correlation</subject><subject>Livestock</subject><subject>Mathematical analysis</subject><subject>Position (location)</subject><subject>Precision</subject><subject>Radiolocation</subject><subject>Spatial</subject><subject>Taggle</subject><subject>Tags</subject><subject>Temporal</subject><subject>Tracking systems</subject><subject>Variance</subject><issn>0168-1699</issn><issn>1872-7107</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kEFL7TAQhYM8wfvUf-AiSzetSdOm6UYQ0fcEwY3uhDCmU821bWomV7j_3lyva1fDMOccznyMnUlRSiH1xbp0YVrgtazyVoq6FEIesJU0bVW0UrR_2CofTCF11x2xv0TrLNCdaVfs-YqTC4ufXzmlTb_lKXAgQiKe3pAvEZ0nH2YeBg4zh00KEyTseYTehzE4SLsrzH6CkacI7v07a0sJpxN2OMBIePozj9nT7c3j9f_i_uHf3fXVfeGU6lKBZqjACFS5VOMaFHKoZdO2TlSdHHSlQSntUEALuh6Ug6buXl6EVLJGYxqljtn5PneJ4WODlOzkyeE4woxhQ1YaqYXptBBZWu-lLgaiiINdYq4et1YKu4Np13YP0-5gWlHbzCrbLvc2zG98eoyWnMfZYe8zoWT74H8P-AJatn-j</recordid><startdate>201606</startdate><enddate>201606</enddate><creator>Menzies, Don</creator><creator>Patison, Kym P.</creator><creator>Fox, David R.</creator><creator>Swain, Dave L.</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201606</creationdate><title>A scoping study to assess the precision of an automated radiolocation animal tracking system</title><author>Menzies, Don ; Patison, Kym P. ; Fox, David R. ; Swain, Dave L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c339t-e8f2a80e30165c5e01f41577c0291f626a336ce0a7a64f3ca549bb01314e88533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Animals</topic><topic>Automation</topic><topic>Correlation</topic><topic>Livestock</topic><topic>Mathematical analysis</topic><topic>Position (location)</topic><topic>Precision</topic><topic>Radiolocation</topic><topic>Spatial</topic><topic>Taggle</topic><topic>Tags</topic><topic>Temporal</topic><topic>Tracking systems</topic><topic>Variance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Menzies, Don</creatorcontrib><creatorcontrib>Patison, Kym P.</creatorcontrib><creatorcontrib>Fox, David R.</creatorcontrib><creatorcontrib>Swain, Dave L.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers and electronics in agriculture</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Menzies, Don</au><au>Patison, Kym P.</au><au>Fox, David R.</au><au>Swain, Dave L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A scoping study to assess the precision of an automated radiolocation animal tracking system</atitle><jtitle>Computers and electronics in agriculture</jtitle><date>2016-06</date><risdate>2016</risdate><volume>124</volume><spage>175</spage><epage>183</epage><pages>175-183</pages><issn>0168-1699</issn><eissn>1872-7107</eissn><abstract>•The mean spatial precision for the ARATS ear tags was ±22m.•Signal propagation effects and meteorological parameters affected spatial precision.•The time between transmissions showed no effect on the spatial precision.
The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (∼5ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28days. 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 ±22m with a SD of 49m with the most and least precise tags having precisions of ±8m and ±51m, 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 17:00h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24h, 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.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.compag.2016.04.001</doi><tpages>9</tpages></addata></record> |
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| subjects | Animals Automation Correlation Livestock Mathematical analysis Position (location) Precision Radiolocation Spatial Taggle Tags Temporal Tracking systems Variance |
| title | A scoping study to assess the precision of an automated radiolocation animal tracking system |
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