Development of a secure underwater sensor suite for real-time environmental monitoring of blue carbon ecosystems
| dc.contributor.author | Singh, Rudra Pratap | |
| dc.contributor.supervisor | Popli, Navneet | |
| dc.contributor.supervisor | Dong, Xiaodai | |
| dc.date.accessioned | 2026-01-05T21:53:12Z | |
| dc.date.available | 2026-01-05T21:53:12Z | |
| dc.date.issued | 2025 | |
| dc.degree.department | Department of Electrical and Computer Engineering | |
| dc.degree.level | Master of Applied Science MASc | |
| dc.description.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. | |
| dc.description.scholarlevel | Graduate | |
| dc.identifier.bibliographicCitation | M. Singh Popli, R. P. Singh, N. Kaur Popli and M. Mamun, "A Federated Learning Framework for Enhanced Data Security and Cyber Intrusion Detection in Distributed Network of Underwater Drones," in IEEE Access, vol. 13, pp. 12634-12646, 2025, doi: 10.1109/ACCESS.2025.3530499. | |
| dc.identifier.bibliographicCitation | M. Gu Kim, Q. Luo, R. P. Singh, N. Kaur Popli and M. Mamun, "Enhancing Underwater Network Security: ML-Based Detection and Prediction of DDoS Attacks in IoUT Networks," in IEEE Access, vol. 13, pp. 190618-190629, 2025, doi: 10.1109/ACCESS.2025.3621594. | |
| dc.identifier.bibliographicCitation | R. P. Singh, B. Singh and N. K. Popli, "Temporal Analysis of Oceanographic Data: Insights into Environmental Variability and Trends," 2024 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), Victoria, BC, Canada, 2024, pp. 1-9, doi: 10.1109/PACRIM61180.2024.10690219. | |
| dc.identifier.uri | https://hdl.handle.net/1828/23042 | |
| dc.language | English | eng |
| dc.language.iso | en | |
| dc.rights | Available to the World Wide Web | |
| dc.subject | Underwater sensor systems | |
| dc.subject | Blue carbon ecosystems | |
| dc.subject | Oceanographic monitoring | |
| dc.subject | Modular underwater hardware | |
| dc.subject | Real-time environmental sensing | |
| dc.subject | Remotely operated vehicles (ROVs) | |
| dc.subject | Internet of underwater things (IoUT) | |
| dc.title | Development of a secure underwater sensor suite for real-time environmental monitoring of blue carbon ecosystems | |
| dc.type | Thesis |