Oil spills devastate marine ecosystems, and conventional cleanup methods are often dangerous and inefficient. Our project, the Oil Recovery and Cleanup Autonomous (ORCA) system, presents a safer, smarter solution. This fully autonomous prototype integrates AI for oil detection (97% precision), LiDAR-based navigation for obstacle avoidance, and an optimized oleophilic surface for collection. Rigorous testing confirmed high skimming efficiencies up to 75.7% and excellent water rejection of 96%. ORCA demonstrates a viable, next-generation approach to oil spill remediation, capable of operating effectively without risking human lives, protecting both our oceans and the people who work to save them.

This project by Kasun Siriwardane titled “The Efficacy of Natural Antimicrobial Compounds in Antifouling and Combatting Biofilm Formation” investigates the effectiveness of natural antimicrobial compounds—tea tree oil, clove oil, and cinnamon essential oil—in preventing biofouling on stainless-steel surfaces in marine environments. Traditional chemical antifouling methods harm marine ecosystems such as fish, and exacerbate water quality, necessitating eco-friendly alternatives. The study submerged stainless-steel cylinders coated with the oils, a chemical agent, and a control in water for 74 hours. Tree Tea oil and Cinnamon Oil demonstrated significant antifouling potential, reducing biofilm accumulation compared to the control. These findings highlight the promise of natural compounds as sustainable antifouling agents, and prompt further long-term studies.

The revolutionary FORDETECT technology has been developed to automatically detect eDNA in water in order to regulate unwanted species and map original species. This technology is still a prototype, which means it has not yet reached its full potential. Our project’s aim is therefore to compare the prototype of the automatic FORDETECT with two manual laboratory methods, PCR and LAMP. After a close examination of the results from the three amplification methods, we conclude that FORDETECT can become much more efficient and economically sustainable than traditional laboratory methods. However, further development of FORDETECT is needed before it reaches that point. We therefore strongly encourage the development of FORDETECT as it can ensure and maintain a high quality of life for aquatic creatures.

Project Current is a collaborative student led project with local industry and Kristiansand International School. The project uses relatively low cost battery driven pressure sensors, and continuously collects data from a local stream in Kvinesdal, where the data is sent wirelessly using Long Range Radio Signals (LORA) to a server. In collaboration with Intoto AS, based at Coverks in Kvinesdal, data on the server is processed continuously and presented.

The goal is to predict floods in the sensor placement area after long term data collection is imputed into a machine learning algorithm.

The municipalities in the region of Haugalandet have looked at the possibility to create a communal source for a spare water supply for the entire region. One possible solution is the lake Storavatnet near Sandbekken in Tysvær. We worked on finding out if Sandbekken could be used or not.

We researched upon the surveillance of plastic pollution in marine resources by the coastline of Norway.

We researched upon the surveillance of plastic pollution in marine resources by the coastline of Norway.

Midtsjoevann is a lake, a public swimming area, and a nature reserve close to the city Ski. Therefore, we wanted to exam

My project started from a fear of the future and the phosphorus-crisis that our planet is facing.