## 4 Results
### Dynamic Setup
#### 4.2.4 TTFF Results by Device Positioning  
The time it takes for a GPS device to gather satellite signals and navigational data to determine its position or fix is known as the time to first fix. Before a GPS device offers the correct position data, it needs three types of data: GPS satellite signals, almanac data, and ephemeris data. This measure is significant because it generally encompasses the measures observed above, such as the signal-to-noise ratio (Cno), the number of satellites, and the accuracy. The less time it takes to perform a fix, the faster the reception of all the necessary values to obtain the position, and thus, the lower the battery consumption since the device can go to sleep mode once the position (fix) is determined. In the following results, it is important to emphasize that for TTFF values, the lower the values, the better, as it is the time it takes to find the geolocation. The warm start startup mode was used for this TTFF measurement. A warm or normal start requires the GPS device to have the following features: timing precision of 20 s, positioning accuracy of 100 km, velocity accuracy of 25 m per second, and correct almanac data. To gather orbital information during a warm start, the device must receive a signal from each relevant satellite [3]. This startup mode was chosen because it most closely replicates the behaviors of an IoT device. * Front Dashboard  
Figure 12 illustrates the results for the TTFF in the locations where the device was on the front dashboard. As seen, the measurement results carried out with the device facing up were relatively similar, with the device with the circularly polarized patch antenna achieving a marginally superior result. This is because this was in a position in which this technology functions more effectively. Figure 12: TTFF results of all device orientations placed on the front dashboard of the vehicle when moving following the path in Figure 4. For TTFF, the lower the value, the better. On the other hand, we could also observe similar results for the face forward orientation, where the linearly polarized antenna booster benefits from this position. The linear polarization devices performed better in both the upside-down and backward positions. This leads to the conclusion that a linearly polarized antenna booster produces better results for the random orientation of a wireless device. * Rear Dashboard  
Figure 13, in this case, displays the outcomes for the rear dashboard position. The results from the route depicted in Section 3.2.2 were averaged. The average result observed for face-up orientation was slightly better for the device using circular polarization (2.3 s better). In the same position, but observing only the city average, it could be observed that the linear polarization device was improved (2.3 s better), which may be due to the negative impact of multi-path for circular polarization. As can be observed, in the other cases, the device with the linearly polarized antenna booster featured better behavior since it took less time to perform the fix (average and city averages were 3.7 and 9.9 s better, respectively  
Under the Seat  
The data in Figure 15 represent the under-the-seat measurement results. In this scenario, if we focus on the _Face-Up_ position, it can be observed that the linearly polarized antenna booster had a much better performance in both the total average and in the city average, with a difference in TTFF of 38.2 s and 73.7 s, respectively. On the other hand, for the _Upside Down_ position, the data obtained showed very similar results for both technologies. Another fact is that compared to the device with the circularly polarized patch antenna, results with the antenna booster fluctuated significantly less between positions. Therefore, the performance with the linearly polarized antenna booster was robust to the position of the wireless device.