A5058796900- Underwater Vehicles and Communication Systems
- Water Quality Monitoring Technologies
- Energy Efficient Wireless Sensor Networks
- Analytical Chemistry and Sensors
- IoT and Edge/Fog Computing
- Fault Detection and Control Systems
- Oceanographic and Atmospheric Processes
- Underwater Acoustics Research
- Water Quality Monitoring and Analysis
Tallinn University of Technology
2020-2024
Monitoring and assessment of coastal river velocities plays a key role in both scientific industry applications. Field measurements are for decision making resource management protection, as well validation numerical models climate change studies. In this paper, Hall effect sensor-based cost effective novel device is proposed measuring direction near-bed currents, water-level. This device, called the Hydromast, provides instantaneous real-world conditions, equipped with communication...
Sensor Networks in harsh underwater environments are prone to faults and anomalies that may lead deteriorated data quality or even failures. This paper proposes a fault-resilient sensor network based on aggregation by updating the measurement error matrix of an adaptive Kalman filter, where is updated using adjusted measured value difference from predicted as well age latest (i.e. latency). A case study real-world harbor water flow monitoring use-case shows advantages proposed method. The...
Sensor networks provide services to a broad range of applications ranging from intelligence service surveillance weather forecasting. Most the sensor are terrestrial, however much our planet is covered by water and Underwater Networks (USN) an emerging research area. One unavoidable increasing challenge for modern technology tolerating faults - accepting that hardware imperfect cope with it. Fault tolerance may have more impact underwater than in terrestrial environment as forgiving,...
The paper proposes a data-driven cross-layer resilient architecture for sensor networks. novelty of the approach lies in combining fault detection across data and network layers into coordinated system health management architecture.The implemented is entirely data-driven: are collected exclusively by functional sensors that part system. Thus, there no need additional hardware resources.The considered include raw layer, processed layer aggregation layer. proposed utilizes hierarchical...