[cosc-grad-students-list] Ruben Dominguez Dissertation - Energy Harvesting and Autonomous Data Collection for Coastal Resilience Monitoring

[Eulenfeld, Menda]

Title:
Energy Harvesting and Autonomous Data Collection for Coastal Resilience Monitoring

Abstract:
Monitoring coastal environments is vital for maintaining ecological balance, supporting sustainable development, preserving economic and cultural value, and ensuring human safety from natural hazards such as flooding, shoreline erosion, and storm surge. Effective monitoring enables risk assessment, early detection, and mitigation strategies that enhance coastal resilience. Common approaches for coastal monitoring include remote sensing, data buoys, autonomous vehicles, and fixed observation stations, which collectively provide valuable environmental insight for researchers and decision-makers. However, these systems are often constrained by limited power availability, high maintenance demands, and restricted mobility, which reduce their effectiveness in long-term and large-scale deployments. These limitations highlight the need for sustainable and adaptive monitoring solutions capable of operating in dynamic coastal environments. This dissertation presents the development of self-sustaining, energy-aware coastal sensing networks that address the challenges of power limitation, communication reliability, and data collection scalability. The proposed framework integrates energy harvesting (EH) sensor nodes with adaptive communication strategies and autonomous data collection mechanisms to enable persistent and resilient environmental monitoring. The system combines battery-less LoRa-based sensor nodes powered by ambient energy sources with a mobile gateway platform capable of autonomous navigation and data retrieval. The research addresses three key objectives: (1) enabling reliable communication and network recovery under intermittent power conditions, (2) optimizing energy utilization through adaptive scheduling and energy-aware operation, and (3) integrating autonomous mobile platforms for efficient and scalable data collection across distributed sensing regions. Collectively, these contributions establish a unified framework for sustainable coastal monitoring that reduces reliance on fixed infrastructure and frequent maintenance. The proposed system supports long-term environmental sensing, improves data availability in infrastructure-limited regions, and contributes to enhanced coastal resilience through scalable and energy-efficient monitoring technologies.

Location:
RFEB 108, June 9th, 10am-11am

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