# Use of Real-Time GNSS-RF Data to Characterize the Swing Movements of Forestry Equipment
## 4 Discussion
Importantly, transmission intervals should be tested and tailored to meet the needs of particular equipment movements rather than relying on a general rule of thumb. From a visual representation standpoint, it is evident in Figure 3 that the 2.5 s transmission interval results in a plotted machine movement track that has smoother curves and higher accuracy representation of precise machine movements and machine component locations to meet operational analysis objectives. Correct classification of elements and overall cycles exceeding 90% for the 2.5 s interval further support this observation, as does the results of the regression based equivalence test. However, higher frequency transponder transmission rates are also more data intensive, requiring twice the data flow and storage capacity. This intensity could be difficult to manage for large projectswith many pieces of equipment, both in terms of data collection and storage, but also real-time analysis, validation, and model optimization. When addressing the ability of the transponder to accurately characterize machine cycles, cycle elements, and angles of swing, the 5.0 s interval was shown to return comparable accuracies to those obtained by the 2.5 s interval transponders, at half the data intensity. In this particular study, the overall sampled time represented only a small portion of what a full productive work day would entail in a commercial logging operation in beetle-killed timber. With the 2.5 s interval, the available storage space needed for each data file will be utilized twice as fast as the 5.0 s interval. Each file saved can consist of up to 9999 data points, after which the device overwrites existing data by default. Therefore, a new file needs to be saved on the handheld receiver every 6.9 h when working with the 2.5 s transmission interval to avoid overwriting and every 13.8 h when working with the 5.0 s transmission interval with three transponders. If additional transponders are used on multiple pieces of equipment, then available storage space will be used up more quickly. This can present problems with data being overwritten during average work days if the file is not saved, e.g., mid-way through the day. Additionally, it was found that the large data pools associated with the 2.5 s interval made analysis and interpretation of the data more cumbersome and time intensive than the longer intervals, an observation also made by [PERSON] and [PERSON] (2015). Depending on the specific application, machines, and desired level of accuracy, incorporating the 5 s interval could return acceptable, though slightly lower, accuracies than the 2.5 s interval. In turn, longer work cycles could be sampled without concern for overwriting data and analysis and interpretation of those data would prove quicker and easier than with the 2.5 s interval if available memory storage and analytical capacity is a concern. When interest is focused on positioning and analysis of precise machine movements where rapid machine movements may be missed by long transmission intervals, the 2.5 s interval likely provides the best option for transmission frequency, or perhaps the study requires more traditional work study methods that relies on direct rather than passive observation. An important consideration with our study is that the Garmin Alpha receiver and positioning transponders were located in open line-of-sight conditions, which may not be typical of many forest stands. No transmissions were obstructed by vegetation, topography, or inter-machine positioning. One hundred percent of the time-stamped positional coordinates were received. Prior experience with GNSS-RF data in operational forestry has shown that GNSS position and radio signal propagation quality (RSSI) can interact in complex ways.