# A Platform of Unmanned Surface Vehicle Swarms for Real Time Monitoring in Aquaculture Environments
## 8 Conclusions  
This paper proposed an aquatic monitoring platform capable of collecting environmental and aquatic data from specific geographical locations. This is performed by using a swarm of USVs and Buoys, combined with a set of sensors. The combination of the hardware and software modules of  
Figure 16: Delay and processing time of the _Collect missions’ data_ message and the _Start Mission_ message.  
this platform is able to provide the following tasks: collect the values from sensors, execute USV tasks in a swarm, deliver the acquired environmental data through multiple communication technologies, and even be capable to request the information directly through a mobile app. The communication technologies comprise IEEE 802.11n (Wi-Fi) and Bluetooth for short-range communications, mission delegation and data collection transmission, and LoRa for periodic reporting.  
With the support of FIWARE technology, an interactive Web-based dashboard has been produced to process and display the obtained environmental and aquatic data measured by the monitoring nodes. Through the same web application, an end-user is capable of creating missions, request the monitoring platforms to deploy specific missions and update their tasks.  
The experimental results have shown that the platform achieves a robust dispatch of sensory data to the central station, either by sending it between the monitoring nodes until it reaches the DTS, with the support of the \(mOVE\) module implemented in each USV and Wi-Fi DTS, or by delivering the sensor data packets through LoRa. Moreover, the results have shown that it is reliable for the USV to deliver the collected data through the \(mOVE\) DTN, as long as the Wi-Fi DTS is reachable by the use of this approach. In the case of a wider distance between the USV and the Wi-Fi DTS, LoRa comes up as good backup to deliver the acquired sensory values to a LoRa DTS.  
To overcome the huge dependence on human-intensive field measurements for data collection in aquatic environments, specifically in aquaculture environments, and the consequence degradation of the water quality responsible for the damage on the proper functioning of aquaculture environments, a system such as the one presented in this work might be very useful as a support platform for aquaculture farmers and workers. This system is able to acquire recent data of the water properties of aquaculture, that may be crucial to take appropriate intervention, allowing the workers to anticipate and mitigate the adverse events that may influence the quality of the water, thus avoiding bad consequences on the fish health.  
As future work, the platform will be deployed in real aquaculture environments. Moreover, the support of multiple swarms will also be researched.  
[PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] designed the aquatic platform and its elements. [PERSON], [PERSON] and [PERSON] implemented the mechanisms, and prepared the case study scenario. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] analyzed the results and wrote the paper. [PERSON] and [PERSON] supervised the entire research process.  
This work was funded by the Project MOBIWISE, POCI-01-0145-FEDER-016426.  
We thank [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] for useful discussions and work in this platform. We also thank the Programa Integrado de IC&DT Centro2020 \"SmartBioR: Valorizacao Inteligente de Recursos Biologicos Marinhos Endogenous num Clima em Mudanca\", Centro-01-0145-FEDER-000018, for its funding related to human resources.  
The authors declare no conflict of interest.