Further, the contribution of SSF to fishing mortality of the exploited stocks is underestimated as only vessels above the length of 10 m are obliged to fill in logbooks. Knowledge of the sector is limited, and information on its fishing effort is sketchy both at national and European Union (EU) level, as VMS is mandatory for fishing vessels from 12 m in length overall and more and AIS from 15 m. The major concern over these fleets is, therefore, their impact on the ecosystem, such as bycatch and discards. SSF mainly involves the use of traditional passive gears to target multiple resource species and operates in coastal areas, where many other users considerably compete for space and resources and where sensitive and priority habitats for fisheries are located.
#Traccar logbook professional#
On the other hand, professional small-scale fisheries (SSF), carried out by vessels of an overall length of less than 12 m and not using towed fishing gear, are excluded from this scenario even though they may comprise a large part of national fleets and a large number of people employed/dependent on these fisheries. Further, vessel positional data and machine-learning analytical algorithms have been used to assess fishing impacts on marine ecosystems , as well as to support spatial planning and management and to monitor compliance to regulations. In large-scale fisheries, the adoption of tracking technologies such as the Vessel Monitoring System (VMS) and the Automated Identification System (AIS) has represented a step toward the application of a more effective ecosystem-based management, contributing to an increase in the information about movements of the fleets, spatial distribution of fishing grounds, and related fishing pressure.
It enables a new monitoring strategy that could effectively include small-scale fleets and support the design of new policies oriented to inform coastal resource and fisheries management. The emergence of a such low-cost and open-source technology coupled to artificial intelligence could open new opportunities for equipping small-scale vessels, collecting their trajectory data, and estimating their fishing effort (information which has historically not been present). Data collected by our first installation are presented, as well as its preliminary processing.
In this context, we designed a cost-effective and scalable prototypic architecture to gather and process positional data from small-scale vessels, making use of a LoRaWAN/cellular network.
The typically low-technological capacity of these small-scale fishing boats-for which space and power onboard are often limited-as well their reduced operative range encourage the development of efficient, low-cost, and low-burden tracking solutions. On the other hand, small-scale fisheries (vessels below 12 m) remain untracked and largely unregulated even though they play an important socio-economic and cultural role in European waters and coastal communities and account for most of the total EU fishing fleet. During the last decade vessel-position-recording devices, such as the Vessel Monitoring System and the Automatic Identification System, have increasingly given accurate spatial and quantitative information of industrial fisheries.
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