BB24.H Mobility Prediction

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Title	Mobility Prediction
Page Title	BB24.H Mobility Prediction
Technology Line	Distributed Cloud Integration
Lead partner	UCC
Leader	Ken Brown
Contributors	UCC, Tyco
Related to Use Cases	SCOTT:WP9, SCOTT:WP15
Description	In this building block we will develop algorithms for real-time mobility prediction of people and objects as they move through a secure facility, exploiting known roles, access control data, and inference from wireless localization. Secure facilities management depends on the identifying the current and future locations of people and critical objects in the facility. People and objects can be located in space using wireless signals and from live data from access control systems (and also from other data sources and sensors). Future locations and trajectories of people and objects can be predicted from live data, from historic use patterns and from known data on agent roles.
Main output	Algorithms for mobility prediction, for use in WP9.
BB category	Service
Baseline	Deployed systems rely on pre-specified roles and schedules for use in order to grant access. Mobility prediction is a current research area, but is not yet linked to access control in deployed systems
Current TRL	TRL 3 – TRL is difficult to classify for this application – lab demonstrations do exist for mobility prediction, but largely assume idealised localisation information on the individuals; larger scale mobility prediction in outdoor environments – e.g. via GPS traces from taxis – also exist; indoors, there are laboratory deployments of wireless localisation systems indoors; we are not aware of lab deployments indoors using wireless localisation and other inputs demonstrating mobility prediction
Target TRL	TRL 5 – our intention is to construct a demonstrator in a real building, using live data from real subjects; it is unlikely that all critical scalability issues will be addressed in the demonstrator.

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