# Developing and Field Testing Path Planning for Robotic Aquaculture Water Quality Monitoring
## 5 Discussion  
These initial results validate the use of drones as a means to monitor water quality levels in an aquaculture environment. With simple software and off-the-shelf hardware, precalculated missions can be sent to drones, which dutifully execute and send data to a cloud service for real-time monitoring. This system has the potential to reduce the cost of farmed fish and address the labor shortage in the North American aquaculture industry.  
Based on our simulations, GLOP and GAM path planning methods were more efficient in creating drone routes for smaller farms (generally less than 200 ponds) and HPP was more efficient in larger farms, with the advantage becoming most evident in the largest simulated farms. This principle seemed to hold during our experiments on a 26 pond farm, as in Figure 10. As was expected, GLOP and GAM performed nearly identically in our flight testing. The HPP routing method was only successful on larger simulated farms due to its simple heuristic, which requires an even spread of pond locations to visit. As a result, HPP generally performed 15-20% less efficiently at the SIU Aquaculture Research Center ponds. Additional testing will also be necessary to further validate the three path planning methods. Testing HPP on a large farm could validate its use as a large-scale path planning algorithm for aquaculture monitoring. Most commercial farms are indeed much larger than the SIU facilities, so its validation would be highly valuable.  
Extrapolating from the data collected for these 26 ponds, estimations for drone range capacity requirements can now be made for other farms. Considering that measuring 9 ponds took approximately 26% battery capacity, all 90 ponds of the SIU Aquaculture Research Center could reliably be measured by 3-5 SplashDrones. Additional data will need to be collected from other facilities to give a better picture of the range requirements in general, as different farms will have different-sized ponds with different distances between them.  
Significant work is still required before HAUCS is ready to support automated farm monitoring operations. The reliability and robustness of automated flights are of the utmost importance, and as demonstrated by our system failures, it is still a work in progress. Additional testing is required to improve the robustness of GPS-guided flight in pond aquaculture setting. Lightweight object avoidance systems for UAVs do exist [43; 44], and may need to be implemented for safety and reliability.  
Inclement conditions such as wind and rain provide an additional complication for HAUCS, as fish ponds need to be monitored particularly closely in these conditions. High winds and precipitation can have unpredictable effects on DO levels because of the stratification of oxygen in the ponds. Combined with the fact that flights may be inhibited or grounded, inclement weather is an important factor to consider in the design of HAUCS. High winds may make certain routes more inefficient if they involve traveling upwind unnecessarily. Path plans may also need to be reconstructed on the fly due to changes in conditions or hardware failures. Real-time monitoring and flight adjustment will be required of HAUCS to operate in all conditions, as well as proper user notification in the event that flights cannot be conducted. An increment weather protocol may also involve the use of protective waypoints for drones to take shelter temporarily without the need to return to the home station.  
Future work on this project may involve using time series prediction algorithms to identify ponds which are most at risk to prioritize them for measurement. This will ease some of the burden of measuring all ponds, focusing only on those most struggling to maintain appropriate DO levels. Additionally, if vision capabilities are added to the HAUCS drones, it may be valuable to consider a mesh network between drones to enable higher bandwidth communication with the base station, as the LoRa links provide relatively low bandwidth.