Development of an Advanced Marine Data Collection and Visualization Platform

Marine scientists and research vessels face significant challenges in efficiently collecting, centralizing, and analyzing vast amounts of hydroacoustic and location data in remote ocean areas, especially when multiple ships are involved. Existing systems lack real-time visualization, local data processing capabilities, and streamlined infrastructure management, hindering timely insights and decision-making.

A mid-sized marine research organization specializing in oceanographic data collection and analysis, operating research vessels equipped with hydroacoustic sensors and IoT devices.

• Create a robust system for real-time collection, processing, and visualization of hydroacoustic and geospatial data from multiple research vessels.
• Implement a local data visualization dashboard accessible via local networks on ships, capable of functioning independently of internet connectivity.
• Automate the deployment and management of cloud infrastructure and IoT Edge modules to simplify setup and maintenance.
• Develop a flexible, containerized architecture supporting diverse technology stacks for efficient deployment across various hardware environments.
• Enhance data analysis capabilities to identify fish species, track vessel trajectories, and monitor oceanographic conditions in real time.
• Improve operational efficiency and data accuracy, supporting scientific discoveries and resource management.

• Real-time data collection and processing from multiple IoT devices and hydroacoustic sensors on research vessels.
• Local dashboard visualization accessible within ship networks, capable of displaying vessel GPS, movement trajectories, hydroacoustic outputs, and fish species identification data.
• Support for local data storage and offline analysis to operate independently from internet disruptions.
• Automated setup and deployment workflows for cloud infrastructure and IoT Edge modules via a command-line utility.
• Containerized deployment architecture using Docker for consistent, portable environments.
• Visualization modules developed with R Shiny for interactive data insights.
• A control panel for device management, status monitoring, and firmware updates.

• Hydroacoustic sensors and GPS modules on research vessels
• Azure IoT Hub for cloud data ingestion and device management
• Emulators and virtual machine setups for testing IoT Edge modules
• Existing scientific data repositories and analytics tools

• Scalability to support additional vessels and sensors with minimal reconfiguration
• High system reliability and uptime, ensuring resilient operation in remote environments
• Secure data transmission and storage, complying with industry standards
• Low latency data processing to enable real-time visualization and decision support
• Ease of use for non-technical users, with straightforward deployment and management workflows

The deployment of this comprehensive marine data collection and visualization system aims to significantly enhance the accuracy and timeliness of oceanographic research. It is expected to improve data acquisition efficiency, reduce operational complexity, and enable sophisticated real-time analysis, leading to faster scientific insights, better resource management, and increased research productivity in remote marine environments.