# Use of Real-Time GNSS-RF Data to Characterize the Swing Movements of Forestry Equipment
## 3 Results  
### Summary  
Transmission interval (\(p<0.001\)), transponder location (\(p<0.001\)), and swing angle (\(p<0.001\)) all affected the correct classification of cycle elements (Table 1). At the grapple, the proportion of verified correct classifications was greater for the 2.5 and 5.0 s transmission intervals than at the heel (Table 2). However, the proportion of correct classification for the 10.0 s interval was slightly higher at the heel than the associated grapple proportion. In all instances, the 2.5 s interval returned higher proportions of success than the other intervals, apart from the 5.0 s interval return element at the heel location. The proportion of correct classifications was least reliable overall for the 10.0 s interval, as expected, followed by the 5.0 s interval.  
Only the 2.5 s interval was able to achieve greater than 90% classification success for a complete cycle and achieved 99% classification success for the Swing Unload element at the grapple location. The 5.0 s interval achieved 90% successful classification at the grapple location. The total swing angles for the duration of the trials captured by the transponders were underestimated. In this instance, the 2.5 s transponder returned the total angle for all 72 trials, and thereby best represented the actual swing totals.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variable** & _Df_1  & **Deviance** & **Resid. Df_2  & **Resid. Dev.**3  & _Pr_ (\(\triangleright\)Chi)4  \\ \hline
**NULL** & & & 2680 & 2054 & \\
**Interval** & 2 & 74.18 & 2678 & 1980 & \textless{}0.001 \\
**Swing Angle** & 1 & 42.38 & 2677 & 1937 & \textless{}0.001 \\
**Location** & 1 & 37.62 & 2676 & 1900 & \textless{}0.001 \\
**Cycle Element** & 1 & 0.04 & 2675 & 1900 & 0.8421 \\
**Interval: Swing Angle** & 2 & 1.00 & 2673 & 1899 & 0.6043 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chi-squared ANOVA table for parameter significance on correct classification proportion.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Location** & **Interval** & **Element** & **Data Points** & \begin{tabular}{c} **Total Angle (Degrees)** \\ **Observed (GPS)** \\ \end{tabular} & **Proportion Correct** \\ \hline \multirow{2}{*}{Grapple} & \multirow{4}{*}{**2.5**} & 1339 & & 0.84 1  \\  & & 769 & 27,360 (23,882) & 0.94 \\  & & Swing Unload & 451 & 13,680 (12,950) & 0.99 \\  & & Return & 318 & 13,680 (10,932) & 0.88 \\ \hline \multirow{2}{*}{\begin{tabular}{c} **5.0** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} 382 \\ Swing Unload \\ Return \\ \end{tabular} } & 382 & 27,360 (21,442) & 0.90 \\  & & Swing Unload & 219 & 13,680 (11,698) & 0.89 \\  & & Return & 163 & 13,680 (9744) & 0.91 \\ \hline \multirow{2}{*}{\begin{tabular}{c} **10.0** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} 188 \\ Swing Unload \\ Return \\ \end{tabular} } & 188 & 27,360 (14,918) & 0.68 \\  & & Swing Unload & 113 & 13,680 (8751) & 0.71 \\  & & Return & 75 & 13,680 (6167) & 0.66 \\ \hline \multirow{2}{*}{\begin{tabular}{c} Heel \\ \end{tabular} } & \multirow{2}{*}{**2.5**} & 1342 & & 0.79 1  \\  & & Swing Unload & 773 & 27,360 (24,455) & 0.82 \\  & & Swing Unload & 443 & 13,680 (12,495) & 0.84 \\  & & Return & 330 & 13,680 (11,960) & 0.80 \\ \hline \multirow{2}{*}{\begin{tabular}{c} **5.0** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} 376 \\ Swing Unload \\ Return \\ \end{tabular} } & 376 & 27,360 (22,740) & 0.86 \\  & & Swing Unload & 227 & 13,680 (12,609) & 0.84 \\  & & Return & 149 & 13,680 (10,131) & 0.87 \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} **10.0** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} 193 \\ Swing Unload \\ Return \\ \end{tabular} } & 193 & 27,360 (15,558) & 0.69 \\  & & Swing Unload & 110 & 13,680 (9195) & 0.71 \\  & & Return & 83 & 13,680 (6363) & 0.68 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary data table.