# Application of RFID to Soil-Erosion Research
## 4 Analysis and Discussion
### Experiment 2  
#### 4.2.1 Survey of In-Situ Particles  
There are several sources of error in the estimation of the locations of the tagged particles, beyond the simple assumption that the true locations are the nominal ones. The method assumes that the best estimate of the location of a particular particle is midway between the first and last \(x\) and \(y\) coordinates at which it is detected by the reader. This assumption means that the detection field is taken to be a circle on the ground with the reader at the centre of the circle, and also assigns the same detection range for all positions of the reader. The detection field of the reader will be a circle on the ground only if the reader and the ground surface are in the same plane. Any ground-surface irregularity or non-alignment of the two surfaces will distort the field of view on the ground surface, and thereby affect the distance over which an RFID can be detected in a particular direction. Such distortion is evident in Figure 5. For the fourth line of particles, the \(y\) coordinate is close to the same plane as the reader, but those to either side are not because of the shallow depression in which the particles were placed. The disparities between the actual and the detected locations of the particles show both greater asymmetry away from the central area, such that all but one of the detected locations of the particles in the two outer lines are to one side of the actual locations, and greater in absolute value. The mean error in location for line 1 is 22.4 mm, whereas that for line 4 is 15.1 mm. The misalignment of the plane of the reader and that of the ground surface leads to an increase in the number of points from which an individual particle can be detected (Figure 8). As pointed out by Reference [12] the shape of the detection zone for an RFID is not a sphere but is a function of its orientation with respect to the reader. Since the orientation of the RFID within the particle is an unknown variable, the isotropic assumption of the detection method is compromised. Using data from the fourth line of particles, we examined the detection range along the \(x\) axis either side of the nominal locations of the particles. The average difference between detection on the left and right side of the nominal locations is close to zero (2.1 mm), as might be expected if the orientation of the RFID within the particle is random. However, the range is from 0 to 56.5 mm, indicating that the orientation of the RFID within an individual particle can have a significant effect on the detection distance. Figure 8: Plot of number of detections of individual particles against their location across the shallow depression in which they were sited. Assuming the RFID tags are, themselves, identical so that the detection range of any individual tag varies only with the quality of the manufactured particles, it might be expected that the greater the number of positions from which any tag can be read the greater is the accuracy with which its true location can be determined. Such an expectation is not borne out by the data which shows a weak (R\({}^{2}\) = 0.097), but statistically significant (\(p\) = 0.001), positive correlation between the number of observations and the error in its location (Figure 9). The possibility that this surprising result arises from the association of increased number of observations (Figure 8) with increased disparity between the planes of the detector and the ground surface was tested by analysing separately the data from the fourth and first line of particles. Neither regression is significant at \(p\) = 0.05, but the R\({}^{2}\) for the fourth line is higher than that for the first line. Consequently, the positive relationship between the error and the number of observations cannot be attributed to this cause. This conclusion is consistent with the fact that the weakest relationship between the error and the number of observations is found for the error in the \(y\) coordinate (Figure 9).