MobiSpaces

MobiSpaces delivers an end-to-end mobility-aware and mobility optimised data governance platform, that concerns the offerings of data acquisition, in-situ processing and all the security- and privacy-related operations.

MobiSpaces envisions a set of toolboxes, suites, and tools that implement the MobiSpaces concept. MobiSpaces identifies the AI-based Data Operations Toolbox, including an additional list of tools, namely the Declarative querying, Decentralized Data Management, and Online Data Aggregator. And the Edge Analytics Suite, including a further list of tools, namely the XAI Prediction Modelling, Edge-driven Federated Learning, and Visual Analytics.

The MobiSpaces platform will be surrounded by a Green & Environmental Dimensioning Workbench for monitoring and advising the processing behavior, ensuring guidelines and legislations towards the zero-carbon footprint and the “do no significant harm” principle.

The project is buliding 5 use cases to test its innovative infrastructure:

• iRoute: The iRoute use case will exploit the e mobility-aware data governance framework using the mobility analytics to drive strategic decisions.
• SmartSense:This use case offers the opportunity to prove the benefits of smart sensing by combining the merits of smart sensing with a platform for secure and trustworthy data management. A smart sensor interprets, manages, processes, combines and fuses different single sensor signals and therefore leads to more accurate, interpretable data to choose and evaluate specific measures to reduce noise and air pollution from traffic. 
• MarineTrafficTracker: Τhe challenge is quickly scaled by the number of devices deployed in the wild and the size of the surveillance area. In single sensor environments, the aim of a robust and accurate vessel tracker is to resolve measurement-to-object association ambiguities, especially in cluttered multi-object scenarios. The deployment of several devices turns it in a multi-sensor, multi-object tracking problem. The increased number of measurements in multisensory systems aggravates the measurement-to-object association problem which arises if multiple closely spaced objects or clutter measurements are present. In this case, the challenge is to combine the results at a regional level providing macro analytics on aggregated data from the edge devices.
• VesselEdge: Vessels serve as distributed mobile sensors,  hence, Machine Learning will happen in-situ (on-board) of the vessels (close to the data production). This will enable efficient data operations across the maritime data life cycle and will lead to better situational awareness, increased safety, and reduction of illegal activity.
• CrowdSeaMapping: This use case will validate how crowdsourced nautical sensor data can be processed and qualified for improving navigational safety at sea using a decentralized data acquisition and Federated Learning approach. The Federated Learning approach will prioritize what information is urgent to share with the centralized server and what can wait until connected to a low-cost communication channel. All vessels with standardized equipment can become a Federated Learning crowdsourcing participant for improving safety at sea. This approach enables different data feedback loops providing different levels of contributions to nautical charts ranging from instant high-priority warnings against hazards to generic verification of existing models and validations of improvements to models.

In addition, MobiSpaces works on a task related to Standardisation Strategy and Activities. This task ensures that the project work uses and is in line with relevant global and standards, as well as identify appropriate sections of the research that are brought into the standardization process or taken upstream to opensource communities.
Activities in the task will contribute towards generating or contributing to representative standards and proposing and promoting them to the appropriate standardization bodies. It also involves identifying and engaging with the relevant standardisation bodies and projects and open-source communities.

Reason for applying to HSbooster.eu services

The MobiSpaces use cases will exploit decentralized/edge processing, privacy-preserving technology, data sharing and interoperability and FAIRification mechanisms.

Throughout the project's lifetime, we aim to get in contact with at least 5 standardisation and legal bodies.

For this reason, we aim to receive the following type of support:

• identify standards and semantic rules that can be adopted in the maritime sector,
• identify and create a connection of relevant SDOs, WG and TC of the maritime sector.