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SpaceTimeLab News

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Big Data and Human Dynamics

Published: Jul 18, 2016 2:05:43 PM

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CPC Closing Workshop - Big Data and Intelligent Policing

Published: Jun 22, 2016 10:09:38 AM

Big Data for Intelligent Policing

Published: Jun 8, 2016 5:13:04 PM

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Research

SpaceTimeLab has a varied portfolio of research that spans our four key research themes, which are Transport and Mobility, Security and Policing, Business Intelligence and Environmental Resilience.

The transportation system is the lifeblood of the city. At SpaceTimeLab, we work to ensure the health of the city by improving the mobility of its citizens and the function of its transportation system. SpaceTimeLab is working on a number of projects (e.g. STANDARD) using large, spatio-temporal transportation datasets to categorise, cluster and profile people  and places.

Examples of our work include:

  • Prediction, simulation and visualisation of urban traffic flows.
  • Identifying flexible travellers and groups using smart card data.
  • Modelling the impact of engineering work and incidents on London tube lines.
  • Developing mobility solutions for cyclists using cycle hire and tracking app data
  • Detecting hybrid travel modes from sparse GPS data.
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Isosurface of traffic congestion in London

The safety and security of the public relies on police agencies maximising their use of the diverse geo-temporal data sources available to them. Collaborating with the Metropolitan Police Service, the Crime, Policing and Citizenship (CPC) project analyses and models the relationship between police activities, crime and public attitudes towards policing. CPC focuses on:

  • Street network based crime prediction
  • Police patrol behavioural analysis
  • Optimal patrol routing in real-time
  • Agent-based simulation for strategic planning
  • Spatio-temporal analysis of public confidence
  • Supply and demand of police patrol coverage
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Examining space-time patterns of police patrolling behaviour

Many facets of business and commerce can be rationalised and improved through an understanding of the spatio-temporal patterns underlying consumer behaviour (e.g. CDRC). Examples include:

  • Insurance fraud
  • Footfall and catchment area estimation
  • Consumer profiling
  • Fleet and logistic management
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Profiling activity around London Underground stations using geolocated Tweets

The Consumer Data Research Centre, works with retail industries to open up their data to researchers in order to provide solutions that drive economic growth and societal improvement.

Advancing knowledge and understanding of natural hazards and developing novel risk assessment methods is a core part of the SpaceTimeLab research agenda. Recent work includes:

  • Hazard susceptibility mapping
  • Hazard risk assessment
  • Flood forecasting
  • Forest fire prediction

SpaceTimeLab is one of 11 partners in INFRARISK, a European Commission project that aims to test the resilience of critical infrastructure networks to a variety of natural hazards.

Our current and past projects include:

Page last modified on 06 jun 16 14:39