# A Platform of Unmanned Surface Vehicle Swarms for Real Time Monitoring in Aquaculture Environments
## 1 Introduction  
Aquaculture is one of the flourishing sectors in the food industry. Global fish production peaked at about 171 million tonnes in 2016, with aquaculture representing 47 percent of the total. With capture fishery production relatively static since the late 1980s, aquaculture has been responsible for the continuing impressive growth in the supply of fish for human consumption [1]. Continuous monitoring of the physical, chemical and biological parameters of aquaculture environments helps not only to predict and control the food production, but also to avoid environmental damage and the total collapse of the production process.  
The monitoring of aquatic environments used to be highly inefficient, time-consuming and with a huge dependence on human-intensive field measurements for data collection. Without the proper use of technology, feeding activities, water analysis must be done in site with hand-held devices or collected for laboratories for further analysis [2]. With this process, the detection of any abnormal condition in the water quality usually happened too late, incurring in expensive costs and complex techniques to revert and stabilize the water quality [3, 4].  
However, with today's advances in technology, it became possible to improve the monitoring process, addressing a larger number of problems related with accessibility, inadequate measurementsor even temporal and spatial scales, increasing the productivity and minimizing the losses by constant monitoring of water quality parameters. Among the technologies that can leverage the monitoring process of aquaculture are the Unmanned Surface Vehicle (USVs) and the Wireless Sensors Networks (WSNs). The first one grants the possibility to collect aquatic samples without the need of human involvement on-site [5], while the second one establishes a communication infrastructure, critical for the transmission of information between the collecting units and the platform owners [6].  
In this context this work proposes an end-to-end mobile solution for real-time monitoring of aquaculture environments. The complete solution includes the data collection equipment, formed by a fleet of USVs equipped with aquatic and outside environment sensors and several communication technologies and, on the back-end side, near shore gateways to receive, store and process the information transmitted by the USVs. Buoys with sensing and transmission capabilities are also included and integrated in the monitoring platform. A web-based platform is used to manage the USVs fleet and monitor the water quality. To alleviate the human-dependency on the data collection process, the aquaculture manager is able to set a list of environmental collection missions (which may include a list of locations and sensing parameters) that will be transmitted to the USVs fleet. With respect to the communication technologies, an Intelligent Network System has been developed, which includes IEEE 802.11n, usually denoted by Wi-Fi, Bluetooth and LoRa. The first ones are used in USV-USV, USV-Buoy and USV-Wi-Fi gateway communications for mission delegation, mission control and the transmission of data collection, while LoRa, due to its duty-cycle restriction, is making use of its long range capabilities for periodic report between the USVs and the LoRa gateway, for mission collection and other important requests.  
The remainder of this paper is organized as follows. Section 2 discusses the related work. Section 3 describes the platform architecture, the functionalities and the Wireless Sensor Kit used. Section 4 presents the multi-communication technologies integrated in the network system, while Section 5 describes the missions' assignment. Section 6 describes the methods implemented in order to acquire data in the platform. Finally, Section 7 presents a case study and discusses the performance results and Section 8 enumerates the conclusions and future work.