The Danish Geodata Agency is lead on a Use Case designed to validate how crowdsourced nautical sensor data can be processed directly onboard vessels, and qualified for improving navigational safety at sea. Using a decentralized data acquisition approach with machine learning, the objective is to collect bathymetric data and to evaluate the required level of prioritization for data transmission to the Danish Geodata Agency.
Navigational charts are crucial for safe marine navigation. However, the perpetual challenge lies in keeping these charts current and accurate amidst dynamic maritime environments. Traditional methods of charting, reliant on periodic and costly surveys, struggle to keep pace with the rate of change in coastal and seabed conditions. Factors such as shifting seabeds, evolving coastlines, and technological advancements continually necessitate updates to ensure navigational safety. The Use case aims to utilise crowd sourced bathymetry (CSB) to enhance nautical products.
Project summary
Mobility in urban and maritime domains greatly affects the global economy and generates a large amount of data, from an increasing number of moving objects. Managing the complete lifecycle of such data requires reliable and privacy-preserving infrastructures, to be in place, so that reliable and secure data operations can be provided. In addition, the utilization of mobility data still has great potential due to the new applications and the environmental footprint caused by mobility (e.g. CO2 emissions, energy consumption).
Motivated by this, MobiSpaces provides an end-to-end mobility-aware and mobility-optimized data management platform, that differs, in that the results of mobility analysis will be used to optimize the complete data path in terms of efficient, reliable, secure, fair and trustworthy data processing. MobiSpaces will extract actionable insights from mobile sensor data and IoT devices in a decentralized manner, offering intelligent transportation services, enforcing privacy restrictions. XAI techniques will be applied at the level of data management and machine learning and support the creation of comprehensive and explainable predictive models. The research results will be validated through five use cases:
iRoute - intelligent public route planning for transport services in urban environments.
SmartSense - intelligent infrastructure that monitors air quality and noise,
VesselTracker - Radio based vessel tracking for non-cooperative vessels
VesselEdge - decentralized data processing on board and improvement of the AIS system
CrowdSeaMapping - Federated Learning for Enhancing nautical Charts
These measures will be continuously adapted and monitored for their environmental sustainability, likewise MobiSpaces will create a widely accepted standard for data processing and analysis, together with a data-rich ecosystem that provides reliable and actionable data that is essential for the growth of the EU's digital economy.