IARPA - HAYSTAC

HAYSTAC aims to establish models of “normal” human movement across times, locations, and people in order to characterize what makes an activity detectable as anomalous within the expanding corpus of global human trajectory data. Success will establish the scientific foundation connecting data, movement, and the expectation of privacy. The Internet of Things and Smart City infrastructures has led to an explosion of data and insight into how people move. This offers the opportunity to build new models that understand human dynamics at unprecedented resolution, which creates the responsibility to understand the expectation of privacy for those moving through a sensor-rich world. However, today’s modeling capabilities focus only on high level dynamics to study population migration, disease spread, or other highly aggregated properties. They cannot capture the fine-grained activities of human life and transportation logistics that drive daily trajectories of movement. The key limitation in

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