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value of 5.06µs. This suggests that it might be the best method of the four considered in this study.

As of the time of writing, WTT only implements the threshold method, using the trigger threshold. Future work could integrate other methods into the app, such as the cross-correlation method.

5.7 FIELD TESTING

A field test of the WTT system was conducted in Rotu forest, in the Northland region of New Zealand. This test was conducted as part of a breeding trial, run by The Radiata Pine Breeding Company (RPBC). WTT was used to measure the ToF velocity on 144 5-year old Pinus radiata trees. The ToF was measured on two opposite sides of each tree using both WTT and also Treetap 4, which is shown in Figure 5.1(j). The trial was conducted by a subcontractor of RPBC, Wharekura Forestry Services Ltd, who have been using Treetap devices in field trials for over 10 years. An image of a measurement being conducted using the WTT system, taken during the trial, is shown in Figure 5.20.

The objective of this trial was to test several aspects of the WTT system including: the device’s strength and robustness, the reliability of the system’s software, the ease of use, the speed of conducting measurements, the battery life of the devices, and the reliability of the ToF results produced by the system.

After completing the trial, minor damage was observed on one of the probes. Some cracking had occurred in the perspex around a grub screw. The circuit board also came loose from its fixing grub screws, enabling it to freely move inside the perspex tube. These issues suggest that some work on the probe housing is required before the system is deployed for large scale field use. The software was found to be reasonably reliable. The Android app did crash a few times during the trial, but this did not prevent the trial from continuing. The trial operators stated that they found the app to be beneficial when compared to Treetap 4. In particular, the ability to tag each measurement with a specific tree ID is very useful. Treetap 4 uses an auto-incrementing numerical tree ID, which makes measuring trees out of order difficult. Additionally, if the operator makes a mistake with the tree ID they cannot correct it immediately, as they can with the WTT system. The operators found that the WTT system was slightly slower to use than Treetap 4. Each individual tap takes slightly longer with WTT, due to the delay of downloading the data to the phone. However, the operators noted that fewer errors due to tree ID mistakes may cause the system to be faster overall. The probe batteries lasted for the duration of the trial. The trial took a total time of 4 hours 50 minutes to complete, and the remaining battery charge of the probes were 67% and 46%, respectively.

A comparison of the velocities measured by the two devices was performed. Fig- ure 5.21 shows the distribution of velocities measured during the trial for both devices.

5.7 FIELD TESTING 129

−200 −150 −100 −50 0 50 100 150 200

Measured speed - tree mean speed (m/s)

0 50 100 150 200 250 Coun ts (a) −200 −150 −100 −50 0 50 100 150 200

Measured speed - tree mean speed (m/s)

0 50 100 150 200 Coun ts (b)

Figure 5.21 Histograms of velocities measured during the field test for (a) Wireless Treetap, and

(b) Treetap 4. To allow comparison between trees, the mean velocity of each tree has been subtracted from each measurement. The standard deviation of each distribution is WTT:σ= 73.34 ms−1, TT4: σ= 48.55 ms−1_. 1600 1800 2000 2200 2400 2600 2800 Treetap 4 velocity (m/s) 1200 1400 1600 1800 2000 2200 2400 2600 Wireless T reetap velo cit y (m/s) y = 0.84x + 35.59 (m/s) R2_{= 0.77}

Figure 5.22 Scatter plot of the velocities measured by Wireless Treetap and Treetap 4 during the

Each measured tree has a considerably different velocity, therefore, the mean velocity of each tree was subtracted so that the variation in velocity measured by the device could be observed. These plots demonstrate that WTT measured a slightly higher variation in velocity across the trial. A scatter plot showing the correlation between the two devices is shown in Figure 5.22. A linear regression line has been indicated on the plot, this demonstrates that WTT has measured a slower overall speed than Treetap 4; the gradient of the fitted line is 0.84. The reason for this finding is unknown, a possible explanation is provided in the following section. Figure 5.22 also contains a number of outlying points, the majority of which fall below the trend line, i.e., indicating that WTT has measured a lower velocity than Treetap 4. It is not possible to tell from this plot which device is in error. However, it is likely that WTT is reporting low velocities, as the measurements taken from the other side of the tree are closer to the velocities reported by Treetap 4. The reason for this error is unknown at the time of writing.

5.8 DISCUSSION 131

5.8 DISCUSSION

Time of flight systems have been available since the early 1990s. However, the form and implementation of these tools has changed little over time. The Wireless Treetap project is an effort to advance the state of the art, through development of a system utilising modern electronic technologies. WTT is the first known ToF system to use a smartphone as an interface device. This chapter demonstrated the feasibility of building a wireless, smartphone based ToF system. A prototype system was constructed, consisting of two probe units and a smartphone running the Treetap app.

A field trial was conducted to evaluate the robustness and performance of the system. The system functioned reasonably reliably, though the app did crash several times. The errors causing these crashes are probably trivial to fix, though the cause of each error needs to be identified before they can be addressed. A simple way to identify such errors is to automatically save the app’s crash log. This should be implemented in future versions of the app. The overall function of the app was well received by the operators. Simple features like allowing tree IDs to be manually input, and erroneous data to be removed, are very useful in the field. Some improvements could be made to the app, such as a simplified means of downloading the measured data. Currently, the data is downloaded from the phone in CSV format using a USB cable. The system may benefit from an automatic data-synchronisation feature, so that data could be automatically sent to a database over the internet. This type of system is more in line with current practices of smartphone software, which rarely uses wired connectivity.

The most concerning outcome of the field trial is the damage observed in one of the probe’s housing. The current housing is probably unsuitable for long term use. Each probe should ideally be robust enough to function for a long time, i.e., a year or more of continuous use. There are several possible options of improving the system’s physical robustness. Different materials could be used for the probe housing. Currently, clear perspex is used for the inner electronics housing. This material is very hard, but quite brittle, especially in locations where small cracks have developed, e.g., around screw holes. Another method of improving the robustness could be to change the way the transducer attaches to the electronics. Currently, the transducer is rigidly attached to the electronic housing. This means that the housing experiences an impulsive stress when the probe is hit into the tree. The housing could be decoupled from the transducer by separating the two using a short length of cable. When performing a measurement, the electronics housing would dangle from the cable, and would be fixed to the cable using either a crimp or a screwed locking-connector. This arrangement would also have the advantage that the operator must grab the transducer at its head when removing it from the tree. With the current system, they can easily grab at the bottom of the probe, potentially applying a damaging torque where the transducer and housing connect.

wired solution. Like Treetap 4, this system could use wired transducers and a box of measurement electronics. The measurement box would connect via Bluetooth to the Treetap app. This would significantly reduce the complexity of the system overall, as most of the electronic subsystems, which currently reside in each probe would only need to be implemented once. It would also eliminate the need for the clock synchronisation system, which represents a significant portion of the engineering effort of the WTT system. Using wired probes in a dense forest has been reported to be a nuisance, as they are easily snagged on branches. However, a conscientious operator is not seriously impeded, as extra care can be taken when moving.

The results of the field trial indicated that WTT measured a slightly lower overall velocity than the Treetap 4 system. This is not particularly concerning, as the measured velocity is strongly dependent on the method used for determining the wave start (see Section 5.6). Currently, WTT is using a fixed-threshold algorithm for determining the wave start, and the sensitivity (threshold) used for performing the field trial was the lowest provided setting. It may be that the threshold was set too low in this experiment, which led to a longer delay due to the signal’s increased rise-time. The method used by Treetap 4 for determining the wave start is not currently known. Future work could explore alternative wave-start algorithms. One advantage of the smartphone-based system is that it is relatively easy to implement a new algorithm, then deploy a new version of the app. Compared to firmware-only systems, like Treetap 4, where upgrading the software is comparatively difficult.

Chapter 6

MEASURING THE STIFFNESS VARIATION IN