1. Prototype module for data gathering to create a database of companies in the maritime sector
Challenge owner: Klaipeda ID
To implement the strategy of the city of Klaipėda 2030, it is necessary to follow and analyze the changing indicators in the defined sectors: maritime economy, bioeconomy, advanced industrial and creative, and service economies – which all benefit from the seashore.
However, the current Classification of Economic Activities (EVRK) system is not effective in identifying companies’ activities and assigning them to specific sectors, such as marine. So, we cannot objectively evaluate benefits, progress, and challenges in these sectors.
One of the solutions steps is to initially identify companies according to their targeted activities. We are looking for a very clear AI solution where from a given list of companies through their web pages AI is searching by provided service keywords.
So basically, AI solution with web scraping. Ideally, the final company list could be integrated with Sodra’s open data, which would immediately return meaningful economic data on these sectors.
Climate change and increasing anthropogenic pressure affect sandy coasts. Both processes and coastal accumulation and erosion can be unfavourable for the socio-economic activities on the seashore. Klaipeda is an example of this process. The Port of Klaipeda, with its jetties, strongly affects coastal processes. In the Port of Klaipeda jetties from 2005 till now, intense coastal erosion was observed in the direct impact zone. The shoreline moved inland by more than 50 m. At the same time, this coastal erosion created a favourable spot for windsurfing at the SE Baltic Sea coast.
The same meteorological conditions, strong (more than 20m/s) westerly winds, with the increased water level, are dangerous for the Port of Klaipeda activities and desirable for the windsurfers. Can you create an alarm system for all extreme wind sports enthusiasts and recreational boat owners to warn them about favourable wind conditions for the wind sports and dangers for the operation boats in the Port of Klaipeda aquatorium? Requirements for the alarm system: collect data on the wind gusts, water level, wave height, predominant wind, and wave direction and analyse available data to prognosis the conditions we are interested.
3. Reduction of carbon dioxide (CO2) emitted during the construction (transportation and installation) phase of the offshore windfarm development
Challenge owner: Ignitis Renewables
For transportation from the marshalling yard to the site and installation of various offshore wind farm components (WTG, foundations, offshore substation platform, etc.), vessels that are capable of consuming up to 50 tons of fuel per day are used.
By investigating the current industry practices, transportation methods, and installation processes that contribute to CO2 emissions to develop innovative and sustainable alternatives or modifications to existing practices that can significantly reduce CO2 emissions during offshore windfarm construction. Consider aspects such as logistics optimization, renewable energy use, and technology advancements.
The solution providers are asked to estimate the environmental benefits of your proposed solutions in terms of CO2 emissions reduction and calculate the potential reduction in CO2 emissions over the construction phase of offshore windfarm development.
Also, assess the feasibility of implementing your proposed solutions within the existing offshore windfarm construction industry. Consider factors like scalability, regulatory requirements, and industry acceptance.
4. Risk Assessment for offshore energy projects in the Baltic Sea region
Challenge owner: Blekinge Institute of Technology
Situation. Increased subsea and offshore energy asset usage may result in additional expensive operations, higher environmental impact, and risk for human resources.
Data-mining excellence. Use data mining approaches to forecast risk, costs, or best time window availabilities for an offshore project development. Find the solution based on historical data and generate a data model as a support tool to measure efficiency and cost reductions for offshore developments.
1. Cargo vessel traffic dataset (AIS dataset, resolution 10 mins )
2. Baltic Sea region on the map (Lat_min: 54.5, Lat_max: 55.4, Lon_min: 13.0Lon_max: 13.5)
5. Data mining excellence – forecasting vessel emissions
Challenge owner: Blekinge Institute of Technology
Ports by using data mining approaches demonstrate excellence in forecasting cargo vessel arrivals for a specific port. We are looking for a solution that designs a data-driven model as a support tool to predict CO2 emissions. The data-driven model should be integrated with external data sources:
- Cargo vessel unloading time
- Cargo vessel CO emissions in parking mode
- Cargo vessel energy consumption while unloading in Kwt/hour
All registered port calls to the following countries: Sweden, Finland, Estonia, Latvia, Lithuania, Poland.
Vessel’s type: all cargo and all tankers (> 65 meters)
Fields: Port ID, Port name, LOCODE, MMSI, IMO, Vessel name, Vessel destination, Vessel type, Time of arrival, Time of departure
6. Online environmental monitoring of water in port areas
Challenge owner: Oslo Metropolitan University
There is a lack of solutions that allow monitoring of water quality and environmental parameters in port areas in a continuous and cost-effective manner. As a result of this data gap, it is very difficult to determine changes in the environment or to document whether certain environmental policy measures are having a real impact. This includes data such as temperature, turbidity, salinity, dissolved oxygen, pH, chlorophyll, underwater noise, images, video, and many more.
To develop a prototype of online environmental monitoring of water in port areas.
THE CHALLENGE LIST WILL BE UPDATED.
Registration for teams (3-5 members) or individual participants: https://bit.ly/Portathon2023Participants
Registration for mentors: https://bit.ly/Portathon2023Mentors
Challenge registration: https://bit.ly/Portathon2023Challenges
The project BLUE SUPPLY CHAINS co-financed by Interreg Baltic Sea Region helps drive the transition to a green and resilient Baltic Sea region.
This article was prepared with the financial support of the Interreg Baltic Sea Region. Klaipėda Science and Technology Park is responsible for the content of the article. Under no circumstances can it be taken to reflect the opinion of the Programme.