# Reducing GPS Error for Smart Collars Based on Animal's Behavior
## 4 Conclusions  
The new proposed method for GPS error correction is applied well for virtual fence technology for goats, in this study. The proposed technique helps to improve the position accuracy of virtual fencing technologies with GPS based smart collars. The proposed method is based on animal behavior in real-time. For our current experiments, we used a smart collar from our previous study [20]. The current study method's implementation was made technically possible with results from the previous study's virtual fence application. Our smart collar transmits 3-D GPS coordinates and 10-D accelerometer sensor data at 1 Hz. The transmitted data is logged and received in the virtual fence application database.  
In the current study, we conducted experiments over a seven-day period for the three different goat behavior activity such as running, walking, and resting (standing, grazing, laying). During the seven days of experiments, the device received several GPS signals with errors. The proposed method was capable of finding incorrect GPS coordinates and determining the accurate position information.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Behaviors** & \
\begin{tabular}{c} **GPS Unfiltered** \\ **Distance (m)** \\ \end{tabular} &
\begin{tabular}{c} **GPS Filtered** \\ **Distance (m)** \\ \end{tabular} & **Actual Distance (m)** \\ \hline \hline running & 493.8 & 361.2 & 345 \\ walking & 527.7 & 350 & 345 \\ resting & 136.2 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Mean average of GPS unfiltered, GPS filtered, and actual distances for all three goat’s behavior during seven days experiment.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Behaviors** & \
\begin{tabular}{c} **Maximum Error Distance (m)** \\ \end{tabular} &
\begin{tabular}{c} **Mean Error Distance (m)** \\ \end{tabular} \\ \cline{2-5}  & _Unfiltered Bias (m)_ & _Filtered Bias (m)_ & _Unfiltered Bias (m)_ \\ \hline \hline running & 153 & 20 & 148.8 & 16.2 \\ walking & 190 & 8 & 182.7 & 5 \\ resting & 162 & 0 & 136.2 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Mean calculated errors (biases) in meters for GPS unfiltered and GPS filtered distances for all three goat’s behavior during seven-day experiment.  
As stated by the results of our experiment, GPS positioning accuracy has improved significantly compared with traditional methods.  
With unfiltered geolocations, the average distance offset is measured by the true position of the smart collar, and the coordinates obtained from the settlers were 110-190 m. Our proposed method significantly affected the results of the mean corrected data bias and unfiltered data bias. The mean bias of the corrected data was 0-16.2 m. The bias of unfiltered and filtered data for each goat behavior are found in Table 5. Besides, the second day experiment results were visualized in Figures 5 and 6.  
The proposed method, however, is mainly oriented for use in virtual fencing systems. The method aids in obtaining true animal positions and reduces incidents of incorrect stimuli administration (sound, electronic, etc.).  
Writing--original draft preparation, software, A.M.; methodology, resources, data curation, A.M., C.W.L., H.K.K., and O.S.; conceptualization, formal analysis, M.-C.K., J.A., and H.J.O.; investigation, writing--review and editing, R.O. and H.S.J.  
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B07043417).  
The authors declare no conflict of interest.