L2M – Advanced Power Electronics Converters for Maximizing Wave Energy Harvesting in Ocean Systems

With its vast untapped potential, wave energy could become the leading source of renewable energy from our oceans. These systems do not produce greenhouse gases, thereby contributing to a reduction in the carbon footprint of electricity generation. With a higher energy density compared to wind, wave energy has significant potential for power generation. However, commercial […]

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L2M – A power converter for hybrid renewable energy systems consisting of wave, wind and solar energy to power remote communities in Newfoundland.

The government of Canada has been developing the Clean Electricity Regulations, which aims to reduce CO2 emissions to 45 percent below 2005 levels by 2030 and net-zero emissions by 2050. One main sustainability goal in the global power sector is to generate clean electricity using renewable energy sources. Hydro, Newfoundland and Labrador’s primary electricity generation […]

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L2M-Advance DC-DC converter for improving performance of underwater electric drone.

This project focuses on developing an advanced DC power converter to improve the efficiency and operational time of underwater drones, which are essential tools for monitoring and managing marine environments. By addressing the limitations of conventional converters—such as energy losses, component stress, and bulkiness—this project aims to enhance battery performance and support longer missions in […]

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L2M – Integrated 3D Reconstruction and SLAM for precise 3D visualization and localization of underwater assets

Our project integrates AI-driven Simultaneous Localization and Mapping (SLAM) with cutting-edge 3D reconstruction techniques to provide precise localization and high-fidelity 3D visualizations of underwater features. This fusion enables accurate measurement of size, depth, and spatial orientation of anomalies, enhancing inspection precision. By adopting this technology, industries can improve inspection accuracy, streamline maintenance, and reduce operational […]

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L2M – Steel Catenary Riser Tracking

This project aims to develop an AI-enhanced autonomous underwater vehicle (AUV) system designed to track Steel Catenary Risers (SCRs) in real time. Accurate tracking of SCRs is critical for maintaining the integrity of subsea infrastructure in the offshore oil and gas industry. The AUV will leverage advanced computer vision and machine learning techniques to continuously […]

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L2M – An Adaptive Instructional System for Simulator-Based Ice Management Training

Our project addresses a critical gap in maritime training, specifically the challenge of developing effective ice management skills in extreme environments. Traditional training methods rely heavily on human instructors, whose expertise is both scarce and costly, limiting the scalability and consistency of training programs. This issue is especially significant in industries like oil and gas, […]

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L2M – AquaFishSense

AquaFishSense addresses the pressing issue of outdated and insufficient information available to fisheries, which impedes their ability to operate sustainably and efficiently. Fisheries face significant challenges due to the lack of real-time data on fish populations and aquatic habitats. This gap in information leads to overexploitation of marine resources, with approximately 34% of global fish […]

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L2M – An adaptive communication module for real-time network switching between satellite and cellular or radio to optimize connectivity for autonomous maritime vessels (MASS).

The project aims to create a mountable communication system, for Maritime Autonomous Surface Ships(MASS) that enables them to switch between satellite and cellular networks like LTE and 5G depending on signal strength automatically. This innovation ensures communication for the smooth and secure operation of unmanned ships. By investigating market requirements and strategic plans this initiative […]

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L2M – AI-Driven Subsea Video Enhancement with Advanced Filtering for Improved Visibility in Challenging Underwater Conditions

This project aims to enhance subsea video quality for improved underwater visual inspection and analysis, crucial for industries like offshore oil and gas, marine research, underwater construction, and maritime security. Leveraging advanced AI and machine learning techniques, we will address challenges like water turbidity, light attenuation, and visual distortions in underwater images. Through the Lab2Market […]

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L2M – Generating electric power from vibrational kinetic energy in ocean industry using piezoelectric VEHs

Hybrid Piezoelectric-Electromagnetic (Piezo-EM) Vibration Energy Harvesters (VEHs) utilizing magnets and nonlinearity present an innovative solution for generating increased energy from mechanical vibrations, offering a sustainable and renewable power source for diverse applications. Our focus lies in creating innovative and highly efficient designs that enable precise tuning of the working frequency based on the specific application, […]

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Computational Modeling of Fluid-Structure-Chemical Interactions in Fish Swimming

Aquatic species, such as fish use effective methods for navigation and propulsion in marine environments. Understanding these functionalities of detecting predators, preys, food, and mates by sensing changes in water velocity and pressure offer valuable insights to design efficient underwater robots. Although underwater odor and chemical cues are crucial for fish navigation, the exact mechanisms […]

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