# Edge Computing Approach for Vessel Monitoring System
## 1 Introduction  
Illegal, unreported, or unregulated (IUU) fishing was about of 30% of the total catch of global fishing in 2010, costing coastal economies billions and depleting fish populations at unsustainable rates [1]. This IUU fishing is estimated to be about USD 10 billion to USD 23.5 billion worldwide, corresponding to 11-26 million tonnes of fishery product [2]. This problem is more severe in developing countries, which face severe consequences such as food insecurity and challenges in addressing this problem. Studies conducted by the UNODC identify the fisheries industry vulnerable to international organized crime [3]. IUU is also associated with environmental crimes damaging marine living resources. IUU fishing affects primarily small-scale fisheries communities in developing countries [4]. IUU fishing is generally considered an environmental crime as it changes ecosystems and affects society as a whole. This problem is difficult to estimate because the illegal activities are performed at high sea, and the assessment of fish stocks is based on estimates [3]. In 2013, the Organisation for Economic Co-operation and Development (OECD) studied the problem of IUU and created a report where it discusses the various approaches used by criminals to evade tax, such as using a false declaration of catch, changing the location of where the fish was caught, providing incorrect description of fisheries products, etc. [5]. The major problem is the high revenue from IUU activities, and the corrective measures should focus on: (1) reducing revenue from IUU fishing; (2) increasing operating costs for IUU vessels; (3) increasing capital costs of IUU vessels; and (4) increasing risk and cost of engaging in IUU activities [6]. The same study found that weak governance arrangements and control process in the fisheries sector is considered the main vulnerability of IUU activities. To mitigate this problem, governments should create stronger policy frameworks and better control processes. A key area for improvement is the tracking of the vessels and the use of data analytics to fast fraud identification. There is a need to have accurate and complete information on vessel activity in the deep seas [7]. To address these issues, the Vossel Monitoring System (VMS) system is proposed. The VMS (MONICAPTM, [[http://www.xeselence.pt/equipamentos/](http://www.xeselence.pt/equipamentos/)]([http://www.xeselence.pt/equipamentos/](http://www.xeselence.pt/equipamentos/))), consists of continuous monitoring equipment (EMC--\"blue box\") installed on fishing vessels, which records and transmits satellite information on the vessel's geographic position, course and speed to a Fisheries Control and Monitoring Center (FCMC) in real-time every 2 h. Geo-referenced information is currently available for all vessels with a total length of more than 12 m and is used for inspection, monitoring, and control of fishing activities. In Portuguese national waters (continental EEZ, Madeira, and the Azores), this universe comprises all coastal trawlers, as well as the great majority of the purse-seine fleet and a percentage of longlines, gill nets, and traps (Regulation (EU) No 1380/2013 of 11 December on the CFP). This information presents great potential for research, allowing the mapping and quantification of fishing activities. It has been used in this industry since the last decade, in the analysis of fleet dynamics, as well as in the estimation of fishing efforts. Underlying this analysis is the identification of the most important phases of fishing operations. The use of VMS points towards this purpose as it requires the knowledge of the operations onboard the different types of vessels, resulting from detailed in loco observations. However, high-quality information regarding the frequency of vessel position records is essential. With a high frequency of records, an experienced observer will be able to identify spatial patterns corresponding to the different phases of the operations.