On May 27, the Intelligence Advanced Research Projects Activity (IARPA) issued a request for information (RFI) for Large-scale Microsimulations with Coherent Activity. Responses are due by 5:00 p.m. Eastern on June 11.
IARPA is seeking information on established datasets and capabilities to create large-scale, long-duration, high-fidelity microsimulations to support human mobility research. This RFI is issued for planning purposes only, and it does not constitute a formal solicitation for proposals or suggest the procurement of any material, data sets, etc. The following sections of this announcement contain details on the specific technology areas of interest, along with instructions for the submission of responses.
Background and Scope
The proliferation of connected devices has generated massive volumes of geo-referenced data and insights on population movement. Human mobility research to model and utilize this data requires significant ground-truth data to evaluate performance of location prediction [1], activity classification [2, 3], anomaly detection [4], transportation optimization [5], and other analytics. To share this movement data openly for public research, it must not contain information infringing upon individual privacy. One avenue to pursue such ground-truthed, privacy-preserving data is through high-fidelity microsimulation.
To leverage simulated data as a basis for algorithm development and ensure future applicability to real world data, the simulation needs to contain realistic characteristics:
- Origin-destination pairs are consistent with human activities
- Demographics of the population are accurate and correlate with appropriate movement
- Movement exhibits temporal variability across time of day, day of week, month of year
- Recurrence of activities for an entity is coherent over time, capturing a pattern of life
- Routing between locations is consistent with local road networks and transportation options
- Scale of population and number trips is appropriate for a given geographic extent
The purpose of this RFI is to identify established datasets, existing data simulation capabilities and ongoing research to create simulated data with coherent activity across these types of dimensions.
Full information is available here.
Source: SAM
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