# Addressing Gaps in Small-Scale Fisheries: A Low-Cost Tracking System +
## 4 Discussion
Regardless of whether the fisher is using nets or traps, a first trip occurs early in the morning (from 01:00 to 04:00-06:00) and a second trip in the evening (13:00-18:00) depending on the soaking time, which instead is related to the fishing gear in use [15; 64]. Further, results highlight how the sensor attached to the hauler is reliable to locate the removal of passive gears, even though an offset error is made between the real rotary motion of the hauler and the transmitted information (due to the timer and the speed at which the token queue fills up). However, improvements in the hauler-acquisition software will be implemented to help in the identification of the gear as well as to guarantee a better estimation of the working time at a high temporal resolution (i.e., seconds). According to the pattern observed in this work, the vessel retrieved and immediately deployed the gear both in the morning and in the evening, even though there were trips in which the gear was only deployed. However, as shown in Table 2, the timing of this fishing behavior can vary in the short-run (e.g., in a week) due to a number of factors such as the gear in use, the weather conditions, and the season/target species [15]. These should be considered while assessing fishing-effort variables. Overall, the preliminary results obtained allow to describe fishing patterns in detail but at the same time underlines that there is still a great deal to be done to understand SSF behaviours at sea and to assess related effort. From a fishery-management prospective, collecting SSF data in this way would indeed be particularly effective to support the application of the ecosystem approach to fishery [65; 66]. In the framework of the ARGOS Interreg Italy-Croatia Project [67], we expect to monitor the routes of approximately 30 boats, over a period of 3 years, exerting their activity as widely as possible along the Marche Region (Italy). We will properly inform end-users regarding the use of data, and a small financial incentive will be available if a fisher will join our initiative. The plan is to track different gear types of the fishery (e.g., trammel net, longline, gill net, pots, and traps) and develop machine-learning models to predict when fishing activity occurs when no sensors could be installed to the hauler and estimate measures of fishing effort. To collect ground truths, researchers will make detailed, timed observations of the different vessel activities, including steaming, shooting, and hauling gear, whilst recording GPS tracks. Increasing the number of vessels equipped, we will be able to characterize SSF fishing behaviors in the study area, related fishing grounds, and seasonal exploitation per gear. Although in recent times monitoring systems based on mobile application represent a tempting and promoted solution [68], especially in those countries where the fishery regulatory system is not more effective [69; 70; 71], we believe that, where possible, a device directly connected to a vessel engine should allow a more-reliable data acquisition. Indeed, looking toward the application of a legislation that provides for the mandatory monitoring of small-scale fishing vessels, it would be unthinkable to rely on official data collection on personal devices, which can be voluntarily turned off or involuntarily damaged.