Last June, the Green and Connected Ports project (Green C Ports), led by the Fundación Valenciaport and funded by the European Commission’s Connecting Europe Facility (CEF) programme, was launched. The project aims to provide a range of digitalization tools and technologies to support port environmental sustainability and performance of port operations in the TEN-T Core Network.
Green C Ports aims to address six business cases which include prototypes and pilot tests that will be used in different European ports and that will serve as a basis to test new technologies, like IoT, big data or predictive analysis using artificial intelligence models.
The first business case, which will take place in the port of Valencia, aspires to integrate different platforms, sensor networks and sources of information to predict the date and time of entry and departure of trucks using predictive analytics and business intelligence tools. In this way, along with achieving high accuracy in the predictions made, it will be possible to determine how many trucks/hour will leave and enter the port at a certain future date and time.
[smlsubform prepend=”GET THE SAFETY4SEA IN YOUR INBOX!” showname=false emailtxt=”” emailholder=”Enter your email address” showsubmit=true submittxt=”Submit” jsthanks=false thankyou=”Thank you for subscribing to our mailing list”]
The second business case will predict the closure of the Port of Venice because of tide, wind, fog. After that it will optimize date and time of entry and departure of ships using predictive analytics and big data tools This prediction system, allowing the ships a safer and more efficient organisation of their trip, avoiding to close the port with very short notice consisting of changes of navigation routes or long waiting times for ships that were about to call at it and as a result, economic and port performance loss.
Business cases 3 and 4 have as a goal to improve air quality and noise in both the Greek port of Piraeus and the port of Valencia. In this matter, various sensors, meteorological databases, optical-imaging cameras and other equipment will be used to predict air and noise quality levels in a near future date and time.
Moreover, the fifth business case will evaluate, in the German ports of Bremerhaven and Wilhemshaven, how ship to shore (STS) crane productivity is impacted by wave agitation, currents and wind. By modelling together big data from different port IT systems, a set of warnings will be sent to interested parties, like terminal operators and sea carriers when reductions in port productivity are expected. When this information is reported, shipping companies will be capable of adjusting the ‘berth window’ that they call at the ports, thus limiting the length of the ship’s stay in port and the number of polluting emissions from these ships.
Lastly, the sixth and last business case will analyze the impact in terms of emissions of a series of goods from the time they are loaded in the warehouse of origin to the time they are unloaded in the warehouse of destination. Sensors and emission cameras will be equipped, in order for carbon emissions to be determined for each of the products that are transported. Due to this pilot case study, companies in the retailing sector will have the ability to inform their customers about the door to door carbon footprint of the products to be bought in the company’s supermarkets.
The project will promote ecological, viable, attractive and efficient maritime transport links, integrated throughout the transport chain, and its application will contribute to rebalancing the EU transport system towards a more sustainable system
Fundación Valenciaport explained.