Automatic identification system is a prominent technology used in warehouses to give managers real time information of their products and assistance to warehouse employees in keeping an accurate inventory record. This kind of assistance is needed as an inaccurate inventory leads to profit loss due to misplacement or other mistakes. This project cooperated with an organization called Stora Enso specifically one of their forest nursery to find a solution to improve their inventory management system. Their current inventory system is a manual process which leads to mistakes occurring that affects the inventory accuracy. This thesis project evaluates automatic identification systems to observe if the technology is a possible solution and aims to answer the research question ”What are the significant impacts an automatic identification system has on an inventory management system?”. From the automatic identification evaluation one system is picked for further evaluation and due to its advantages radio frequency identification (RFID) is picked. To evaluate RFID in a warehouse setting a discrete-event simulation was created that simulates the forest nursery’s warehouse. The simulation is then used to evaluate the impact of different RFID implementations and their respective cost. The simulation results show that just a simple RFID implementation can improve inventory accuracy and remove some of the mistakes a manual system has with a relatively low direct cost. It also shows that a full RFID implementation that gives full visibility of a warehouse can almost remove inventory mistakes however the cost analysis shows that it requires a large investment.

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Levels of underwater noise in the open ocean have been increasing since at least the 1960s due to growth in global shipping traffic and the speed and propulsion power of vessels. This rise in noise levels reduces the range over which vocal marine species can communicate, and can induce physiological stress and behavioural responses, which may ultimately have population-level consequences. Although long-term noise trends have been studied at some open-ocean sites, in shallower coastal regions the high spatiotemporal variability of noise levels presents a substantial methodological challenge, and trends in these areas are poorly understood. This thesis addresses this challenge by introducing new techniques which combine multiple data sources for ship noise assessment in coastal waters. These data include Automatic Identification System (AIS) ship-tracking data, shore-based time-lapse footage, meteorological data, and tidal data. Two studies are presented: in the first, AIS data and acoustic recordings from Falmouth Bay in the western English Channel are combined using an adaptive threshold, which separates ship passages from background noise in the acoustic data. These passages are then cross-referenced with AIS vessel tracks, and the noise exposure associated with shipping activity is then determined. The second study, at a site in the Moray Firth, Scotland, expanded the method to include shore-based time-lapse footage, which enables visual corroboration of vessel identifications and the production of videos integrating the various data sources. Two further studies examine and enhance basic analysis techniques for ambient noise monitoring. The first study examines averaging metrics and their applicability to the assessment of noise from shipping. Long-term data from the VENUS observatory are empirically assessed for different averaging times and in the presence of outliers. It is concluded that the mean sound pressure level averaged in linear space is most appropriate, in terms of both standardization and relevance to impacts on marine fauna. In the second study, a new technique for the statistical analysis of long-term passive acoustic datasets, termed spectral probability density (SPD), is introduced. It is shown that the SPD can reveal characteristics such as multimodality, outlier influence, and persistent self-noise, which are not apparent using conventional techniques. This helps to interpret long-term datasets, and can indicate whether an instrument’s dynamic range is appropriate to field conditions. Taken together, the contributions presented in this thesis help to establish a stronger methodological basis for the assessment of shipping noise. These methods can help to inform emerging policy initiatives, efforts to standardise underwater noise measurements, and investigation into the effects of shipping noise on marine life.

<p>An ethnographic study loosely informed by the theoretical framework of distributed cognition was carried out in order to describe how mariners have adopted the Automatic Identification System (AIS) in their work practice, or"made the technology their own". AIS is a transponder-based identification and communication system that allows ships to automatically identify and track each other. In addition to facilitating the identification and tracking of ships, objectives behind the introduction of AIS are to"simplify informational exchange", and"provide additional information to assist situation awareness". Participant observation and interviews were made at four different ships, as well as at two shore stations. A focus group was also held at a maritime conference. The study gave some interesting results. For example, a Problem of Public Information Loss was identified. It is tentatively suggested that this problem has been overlooked partly because of a widespread but impoverished model of communication which does not account for the role of side-participants in a conversation. It is concluded that more research needs to be done on maritime work and the use of new bridge technology.</p>

Kaohsiung Harbor is one of the major commercial ports in Taiwan, located at the hub of northeastern and southeastern Asia shipping lanes. Therefore there are a considerable number of commercial shipping channels distributed around Kaohsiung Harbor. The security of Kaohsiung Harbor becomes more difficult to defense than others due to the complexity of channels. In this study, Automatic Identification System (AIS) system is used to collect the ships information from June 1, 2010 to June 30, 2011. The collected AIS data were decoded, converted, corrected, integrated and analyzed systematically, which will become the base of future database. The information of the AIS includes Maritime Mobile Service Identity (MMSI), latitude and longitude, heading, course, speed, and others. The activities of ships can be monitored by AIS, so the density and distribution of ships on each major channel can be obtained by grid computing. By the results of one-year AIS data, three major shipping channels of Kaohsiung Harbor can be identified, which are north-western, north-southern, and east-western. Based on this kind of long term shipping statistics, possible novel harbor security defense may be founded. Although the AIS was designed to monitor the ship activities, but it can be viciously shut down, or signal is out of range sometimes, then it will become the possible security breach. Nevertheless, ships at sea will generate certain kind of noises, such as from engine and propeller. With efficient propagation of sound waves in water, acoustic technology may compensate the limitations of AIS, to be a feasible method of detecting unknown ships. In this study, acoustic modeling code ¡§Acoustic Module for Sea-surface Noise¡¨ (AMSN) is applied by using the ship position information from AIS, to calculate the related underwater noise sound field of Kaohsiung Harbor. Discussions were made on the dependence of noise level variation with ship density. As a conclusion, with sufficient understanding of sound field statistics of harbor, any anomaly of noise level can be an indication of hostile intrusion, thus harbor security can be further assured.

In the long term it is beneficial to a country's economy to exploit the maritime environment surrounding it responsibly. It is also beneficial to protect this environment from poaching and pollution. To achieve this the responsible parties of a country must have an awareness of what is transpiring in the maritime domain. Synthetic aperture radar can provide an image, regardless of weather or light conditions, of the ocean showing most vessels therein. To monitor the ocean, using synthetic aperture radar imagery, at the lowest cost would require large swath synthetic aperture radar imagery. There exists a trade-off between large swath imagery and the image's resolution resulting in the largest swath image having the poorest resolution. Existing research has shown that it is possible to use coarse resolution synthetic aperture radar imagery to detect vessels at sea, but little work has been done on classifying those vessels. This research aims to investigate the coarse resolution classification information gap. This is done by using a dataset of matching synthetic aperture radar and ship transponder data to train a statistical classification algorithm in order to classify or estimate the length of vessels based on features extracted from their synthetic aperture radar image. The results of this research show that coarse resolution (approximately 40 m per pixel) synthetic aperture radar imagery is able to estimate vessel size for larger classes and provides insight on which vessel classes would require finer resolutions in order to be detected and classified reliably. The range of smaller vessel classes is usually limited to ports and fishing zones. These zones can be mapped using historical vessel transponder data and so a dedicated surveillance campaign can be optimised to use higher resolution products in these areas. The size estimation from the machine learning algorithm performs better than current techniques. / Dissertation (MEng)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

Observation of marine animals in their environment – whale-watching – has grown greatly in recent years, bringing risk to the animals. Of particular concern are harmful impacts on marine mammals, some of which are endangered. As a result, regulations have been developed for their protection, but these conservation measures require enforcement across a broad geographic region, which is difficult due to limited monitoring resources. A ship-borne information transmission system called AIS – Automatic Identification System – can provide information-rich marine vessel movement data that can be used to passively monitor vessels engaged in viewing wildlife, aiding regulatory bodies with compliance enforcement. Few studies explore the use of AIS data to determine when vessels are engaged in wildlife-viewing, and as such little guidance exists on how to implement classification models appropriately. The objective of this thesis is to use AIS data to evaluate the accuracy and utility of existing classification models to detect vessels engaged in observing wildlife, and determine whether information about species being observed can be extracted. Using a control set of observed cetacean encounter data, three classification models were statistically assessed. From this, a hidden Markov model was chosen for detailed analysis in the vicinity surrounding Vancouver Island, B.C., Canada. The resulting analysis concluded that a hidden Markov unsupervised classification approach was feasible for detecting vessel behaviours and differentiating species type. These findings suggest AIS can aid managers and the commercial whale-watching industry in making informed decisions regarding conservation regulations and their compliance. / Graduate / 2022-08-12

An ethnographic study loosely informed by the theoretical framework of distributed cognition was carried out in order to describe how mariners have adopted the Automatic Identification System (AIS) in their work practice, or"made the technology their own". AIS is a transponder-based identification and communication system that allows ships to automatically identify and track each other. In addition to facilitating the identification and tracking of ships, objectives behind the introduction of AIS are to"simplify informational exchange", and"provide additional information to assist situation awareness". Participant observation and interviews were made at four different ships, as well as at two shore stations. A focus group was also held at a maritime conference. The study gave some interesting results. For example, a Problem of Public Information Loss was identified. It is tentatively suggested that this problem has been overlooked partly because of a widespread but impoverished model of communication which does not account for the role of side-participants in a conversation. It is concluded that more research needs to be done on maritime work and the use of new bridge technology.

I Nyköping utövar försvaret telekrigsövning för målflyg vilket Saab i Arboga är en del av. Telekrig är ett “digitalt krig” där syftet är att störa ut elektrisk utrustning, exempelvis störa ut radarfunktionen så att en eventuell fiende inte ska dyka upp på densamma.  Syftet med uppgiften var att tillförse målflygen med ett kommunikationssätt som underlättade kommunikationen vid en övning. Detta kommunikationssätt måste vara hemligt då man aldrig kan veta vem som lyssnar på informationen som skickas. Komradion behövde en ersättare som både var snabb, säker och enkel att använda. Kommunikationen skulle komma att ske via transpondrar som är installerade i samtliga övningsflygplan Nyköping tillhandahåller. Dessa transpondrar skickar och tar emot den vanliga AISinformationen vilket bland annat beskriver riktning och bäring för planet.  Del ett av uppgiften gick ut på att undersöka dessa transpondrar för att se om det fanns möjlighet att skicka egendefinierade meddelanden. Denna uppgift löstes genom att koppla upp två datorer till transpondrarna och pratade med dem via IP.  I del två av uppgiften ingick det att ta fram funktioner, ramverk och stödprogram för meddelandekommunikation. Genom att ta fram en programvara som grundades på lösningen i del ett så kan vi ta emot och sända ut meddelanden på radionätet vilket effektiviserar kommunikationen vid telekrigsövningar där flertalet enheter deltagar. Vi tog fram ett programvara som agerade hjälpprocess till programvaran i del ett. Programvaran genererar hemliga kodord till varje textkommando så att endast ett kodord behöver transmitteras över nätet, där kodordet matchas mot en textstäng på mottagande sida.  I sista delen av uppgiften, som vi skulle göra om tid fanns, skulle vi göra en applikation som gjorde detsamma som programvaran i del två gjorde fast på en surfplatta. Detta löste vi genom att innan vi började på del två använda ett tillägg som tillät oss att köra programvaran på både dator och surfplatta.

The term Big Data has been gaining importance both at the academic and at the business level. Information technology plays a critical role in shipping since there is a high demand for fast transfer and communication between the parts of a shipping contract. The development of Automatic Identification System (AIS) is intended to improve maritime safety by tracking the vessels and exchange inter-ship information.  This master’s thesis purpose was to a) investigate in which business decisions the Automatic Identification System helps the shipowners and operators (i.e., users), b) find the benefits and perils arisen from its use, and c) investigate the possible improvements based on the users’ perceptions. This master’s thesis is a qualitative study using the interpretivism paradigm. Data were collected through semi-structured interviews. A total of 6 people participated with the following criteria: a) position on technical department or DPA or shipowner, b) participating on business decisions, c) shipping company owns a fleet, and d) deals with AIS data. The Thematic Analysis led to twenty-six codes, twelve categories and five concepts. Empirical findings showed that AIS data mostly contributes to make strategic business decisions. Participants are interested in using AIS data to measure the efficiency of their fleet and ports, to estimate the fuel consumption, to reduce their costs, to protect the environment and people’s health, to analyze the trade market, to predict the time of arrival, the optimal route and speed, to maintain highest security levels and to reduce the inaccuracies due to manual input of some AIS attributes. Finally, participants mentioned some AIS challenges including technological improvement (e.g., transponders, antennas) as well as the operation of autonomous vessels.  Finally, this master’s thesis contributes using the prescriptive and descriptive theories and help stakeholders to find new decisions while researchers and developers to advance their products.