Position and movement analytics for geospatial business intelligence

Analytics Engine

Visual analytics enable optimal customer targeting by analysing location and likely travel patterns for consumer marketing and cost-effective sustainable targeting.
Combining geospatial data with consumer marketing information, customers can dynamically visually correlate demographics with location.
…worldwide appetite for business intelligence platforms, analytic applications and performance management software in 2008 increased 21.7% to $8.8 billion.

- GARTNER 2009

HOME > Products > Analytics Engine

The VisTracks Analytics Engine offers solution developers a powerful library of statistical routines that are designed to provide insights into patterns that underlie large volumes of spatial and temporal data. Given several days of position information from instrumented vehicles, for example, the Analytics Engine can determine several metrics, including most frequent routes, average idle times, common stop points, etc. that can help a planner optimize asset usage.

The Analytics Engine integrates tightly with the other components of the VisTracks architecture to enable solution developers to easily provide their customers with powerful statistical insights. Data captured through the Tracking Engine, for example, can be easily forward to the Analytics subsystem for analysis, with the results then displayed visually within the application interface.

The VisTracks Analytics Engine integrates the “R” statistical programming language for partners to extend analytical capability even further.

With VisTracks Analytics Engine, you can:

  • Gain insight into patterns of asset movement.
  • Extract salient features from large volumes of motion data.
  • Identify trends in data and predict potential future directions.
  • Increase decision correctness and responsiveness based on real-time analytics.
  • Develop early warning and alerting from monitoring real-time data.
  • Create sophisticated regression models that predict likely future system behavior.
  • Determine excessive system “idle” or “use” times and optimize energy consumption and cost.
  • Compute “most frequent” or “anomalous” vehicle or asset stop points.
  • Understand deviation between planned and actual routes.