Earlier in this special we elaborated on the idea of big data. The maritime industry is not yet very familiar with the ins and outs of this kind of data use. Nevertheless, a number of projects were conducted during the last few years which focussed on the use of big data.
A research project of TNO in cooperation with fishing company Jaczon and Farsounder Inc regarding sonar systems in the fishing industry has recently become of relevance again due to the changed regulations in the area of bycatch. This bycatch is no longer allowed to be thrown back into the sea, which among others takes a lot of space aboard.
“Where very specific catch quota become more and more important, TNO was asked to develop and propose an innovative tool capable of assisting the fish industry, from the fisherman to the deciding authorities, by giving insight on fish schools and shoals” , states Benoit Quesson, SOFIC project leader at TNO .
A lot of fishermen already used sonar equipment to spot where the fish is, but now the equipment has been developed with the use of big data in order to spot the kind of fish.
Recognising fish
In the project Sonar for Fish Classification (SOFIC) a prototype of a sonar detection device was developed and tested. The SOFIC Demonstrator is able to recognise four types of pelagic fish, which are herring, mackerel, horse mackerel and sprat. With the help of set algorithms about the fish’s behaviour, among others based on information provided by biologists, in combination with existing sonar equipment delivered by Farsounder, a prototype was developed.
Cheryl M. Zimmerman, president of FarSounder adds: “We believe that this project will be of significant interest to anyone concerned with ocean resource management. This technology can help the fishing industry take another step towards preventing unintentional bycatch.”
The prototype was installed on a Jaczon fishing vessel in May 2013. “Selective fishing is one of the possible solutions in which Jaczon is investing to achieve its aims for sustainable fishing” , says Eric Roeleveld , operation manager of Jaczon.
The testing phase was completed in the summer of 2014. The results showed that the Demonstrator was able to recognise the kind of fish in 80 per cent of the cases. Combined with the knowhow of the fishermen about the influence of the weather and the direction of the water flow, and to their decision to fish or not to fish the system was 100 per cent accurate in preventing any bycatch. A great example of using data that is already available, combining it with relevant information and manipulate it in that way the needed information is generated, according to TNO’s Dan Veen. Jaczon is still using the system while fishing.
Connecting the logistic chain
As previously explained, the ports of the Netherlands make use of the data exchange system Port Community System (PCS) developed by Portbase. In 2011 the Nextlogic programme was kicked off by the Port of Rotterdam in cooperation with several market parties in the shipping industry.
Earlier programme manager Teunis Steenbeek said: “At the start of the project we said ‘doing nothing is not an option’, the inefficiencies and unreliability will stay and will get worse.”
Rien Geurts, managing director at BCTN, an inland terminal operator , added: “The most important thing for us is that our customers can rely on us. Reliability means we can effectively predict when a container arrives in the hinterland from the seaport, but the alignment between terminals and shipping companies is difficult.”
The solution Nextlogic wants to offer is based on three pillars: neutral integral planning of terminal and depot slots, call optimisation and performance measurement.
Transparency
The first pillar consists of a neutral integral planning of terminal and storage slots in the port of Rotterdam. “At the moment the planning of the slots is bilateral, this needs to become integral. Therefore a system based on PCS, which offers logistical information to relevant parties, is developed that will be the information platform for the brain. The brain is a set of mathematical algorithms that create an optimal planning for all the different companies that use each others services. However, in order for the information platform, and therefore the brain, to work the relevant companies need to put actual data into the platform and in order for it to be up-to-date they also need to keep updating their information”, says Steenbeek. The brain will be de- veloped during 2015 and in 2016 the brain and the platform will undergo testing.
Jouke Schaap, commercial manager at APM Terminals comments added: “The base of the whole Nextlogic project is creating transparency. It is important to show the whole chain how the performance has been up until now. Through measurements and insight it is possible to have a dialogue with the sector.”
Amsterdam canals
Then thirdly, Waternet Amsterdam, the organisation among others responsible for maintaining the Amsterdam water network, wanted to gain more insights in the activities on the Amsterdam canals for three purposes. Firstly, to know who is sailing on what; secondly, to gain insight into how crowded the canals are at any point of time and if there are any delays at present, and lastly, to ease the enforcement of the rules and regulations. Tourist vessels are for example banned from certain parts of the canals. With the new data platform a violation can be spotted right away.
However, not only Waternet itself can benefit from the data but waterway users as well. Therefore the VaarwaterApp (in English: waterway app) and a Vaarkaart (in English: canal navigation map) available on the site of Waternet, have been developed. With these tools waterway users can for example spot areas in the canals where it is quiet, or too busy or blocked and adapt their sailing route. The Vaarkaart gives among others predictions about the speed and number of vessels.
Combining data
How is it possible to receive all this different kind of information? In order to create the right output of all the data, TNO became involved in the project. On 17 spots in the Amsterdam canals they placed sensors, which can measure the presence of boats, their sizes and much more. This information was connected to the AIS information, and data like weather information and knowledge about obstructions were used to be able to make the right predictions in a data platform.
Veen : “This project has been the perfect example to show how you can connect your own data with public information in order to gain the most and to service different people with the use of the same data.”
Anne Kregting