L2M – AI-optimized RF energy harvesting and Simultaneous Wireless Information and Power Transfer (SWIPT) platform

Ocean technology companies and research organizations rely on autonomous sensors, buoys, and communication nodes to monitor marine environments and support offshore operations. While these devices provide essential data, their dependence on batteries creates high servicing costs, logistical challenges, and limited deployment lifetimes in harsh marine conditions. Overcoming these limitations is critical for enabling sustainable, long-term ocean monitoring.
This project will develop a wireless RF energy harvesting and Simultaneous Wireless Information and Power Transfer (SWIPT) system tailored for marine applications. By delivering both power and data wirelessly, the approach aims to eliminate battery dependence, reduce costs, and enable continuous, scalable sensor operation. Unlike incremental improvements in battery technology, this solution offers a transformative approach to powering remote ocean platforms.
The research objectives are fourfold: (1) model and simulate RF energy harvesting and SWIPT systems; (2) design machine learning algorithms for adaptive impedance matching, beamforming, and scheduling; (3) integrate RF and ML simulations to test system performance under dynamic marine conditions; and (4) validate the framework using representative marine sensor case studies. In parallel, the project will explore biodegradable housing materials to reduce environmental impact and align with sustainability goals.
By combining RF engineering, AI-driven optimization, and application-focused validation, the project will deliver a proof-of-concept system that advances ocean monitoring capabilities. The outcomes are expected to reduce operational costs, extend device lifetimes, and strengthen Canada’s leadership in ocean innovation, supporting applications in fisheries, offshore energy, and climate research.

Faculty Supervisor:

Lihong Zhang;Reza Shahidi

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Artificial Intelligence; Information and Communications Technology; Sustainability & the Environment

University:

Memorial University of Newfoundland

Program: