Rudra Pratap Singh

Topic

Development of a Secure Underwater Sensor Suite for Real-Time Environmental Monitoring of Blue Carbon Ecosystems

Department of Electrical and Computer Engineering

Date & location

• Friday, December 12, 2025

• 11:30 A.M.

• Engineering Office Wing

• Room 430

Reviewers

Supervisory Committee

• Dr. Navneet Kaur Popli, Department of Electrical and Computer Engineering, UVic (Co-Supervisor)

• Dr. Xiaodai Dong, Department of Electrical and Computer Engineering, UVic (Co-Supervisor) 

External Examiner

• Dr. Sudhakar Ganti, Department of Computer Science, University of Victoria 

Chair of Oral Examination

• Dr. Dante Canil, School of Earth and Ocean Sciences, UVic 

Abstract

The health of Canada’s blue-carbon ecosystems—kelp forests, seagrass meadows, and salt marshes—plays a vital role in marine biodiversity and long-term carbon sequestration. Yet these ecosystems are increasingly vulnerable to anthropogenic and natural stressors such as temperature variation, pH fluctuations, heavy-metal pollution, and hydrocarbon extraction. Traditional monitoring methods, relying on sporadic field sampling and manual analysis, fail to capture the temporal and spatial complexity of these changes. This thesis, Development of Machine Learning-Based Techniques for Monitoring and Analyzing the Effects of Natural and Manmade Stressors on Canada’s Blue Carbon Ecosystem Using a Secure Underwater Communication Suite, presents a comprehensive hardware-driven approach to address these gaps. The research involves the design, fabrication, and laboratory validation of a modular underwater sensor suite deployed via a Blue Robotics ROV platform to collect high-resolution oceanographic data. The integrated system measures temperature, salinity, dissolved oxygen, pH, turbidity, and chlorophyll concentrations through a network of calibrated probes, ensuring precise and repeatable environmental sensing. 

To support continuous operation, a secure underwater communication and data-handling framework was developed using a hybrid Ethernet-acoustic link and lightweight encryption protocols to preserve data integrity and mitigate cyber vulnerabilities within the Internet of Underwater Things (IoUT). Extensive laboratory testing in controlled aquatic environments demonstrated stable sensor calibration, minimal noise drift

(< 0.05% FS), and consistent data throughput at depths up to 1 m. Complementary studies explored intrusion detection and federated-learning frameworks for distributed underwater nodes, strengthening the resilience of the proposed communication network. 

The system enables near-real-time environmental monitoring and data synchronization between underwater nodes and surface control units. By combining reliable hardware sensing with secure data transport, the work advances Canada’s capacity for sustained observation of blue-carbon habitats. The results contribute both an open hardware architecture for scalable underwater sensing and a validated communication protocol for secure marine data acquisition—foundations that can inform future autonomous monitoring networks and adaptive management strategies for coastal ecosystems.