Smuggle Detection and Notification of Local Fishing Boats Using an Android phone

Abstract

Currently it has become a diplomatic issue that fishermen sail over Sri Lankan frontiers and enter Indian border and also involve in illegal activities such as smuggling, drug-dealing, etc. Usually we hear one or two arrests of fishermen of both countries by both naval security guards so frequently. But when thousands of fishing boats are doing fishing at the same time it is hard to stop illegal activities as well. Also a major concern for both countries has been smugglers trying to hide out between other fishermen in sea. To find a suitable solution for the issues, a survey was carried out to identify different patterns of fishermen. The survey was carried out as face-to-face interviews as well as in questionnaire form by conducting fishermen, civilians and SL Navy officers. The analysis of the survey results helped a lot to improve on our insight on real issues faced by fishermen and SL Navy. This research effort was targeted on identifying different patterns of fishermen when they do fishing. Also different patterns of fishing boats were analysed to identify abnormal behaviours. Relevant Sri Lankan authorities such as SL coast guard and SL Navy can now see fishing boat behaviours on identified abnormal patterns. Also there were steps taken to alarm fishermen as well as relevant local authorities like Sri Lankan coast guards when fishing boats accidentally cross border as well. Using cloud based hosting services together with GPS technology and with an Android application; it was successfully managed to prove that there is no technical barrier in identifying abnormal behaviours of fishermen. Also feasibility of the research was proved through a working sample as well. A client application was written to capture GPS location details and sent along with a vessel and the journey of the vessel was traced through GPS technology and through server side data. The sample produced us some insight on identifying certain behavioural patterns. Through that it was proved that identifying an abnormal pattern is technical feasible using an Android phone.