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.

Technologies used

MobiSpaces delivers an end-to-end mobility-aware and mobility optimised Data Governance Platform. It is surrounded by a Green & Environmental Dimensioning Workbench for the monitoring and advising of the processing behaviour, making suren guidelines and legislations are complied with towards minimising the environmental footprint. MobiSpaces envisions a set of toolboxes, suites, and tools that implement the MobiSpaces concept in its use case, see them showcased below.

Declarative Querying

Declarative Querying

Online Data Aggregator

Online Data Aggregator

Edge-driven Federated Learning

Edge-driven Federated Learning

Visual Analytics

Visual Analytics

What will MobiSpaces improve?

Performance in re-scheduling the service to peak period will be improved in the following Key Performance Indicators:

>85 %

data to object association accuracy

>80 %

data to track association accuracy

>30 %

data to server flow reduction

Who is involved?