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Abstract – Pattern of Life (POL) analysis constitutes a subset of Activity-based Intelligence (ABI) - understanding those complex spatiotemporal contexts within which entities (e.g., cancer cells, people, etc.) move about and interact, normally-but not always- with a type of recognizable regularity.
6 Οκτ 2021 · Modeling patterns of life that scale along all three dimen-sions requires new approaches and algorithms, built on artificial intelligence foundations. We outline three AI re-search areas on which future solutions could build. Pattern recognition. Instantiating an accurate, specific POL model depends on close observation of actual patterns of life.
SRI has developed a system to automatically analyze the Pattern of Life (PoL) of ports, routes and vessels from a large collection of AIS data. The PoL of these entities are characterized by a set of intuitive and easy to query semantic attributes.
Moving object data analysis and more specifically Pattern of Life (PoL) analysis aims to understand behaviors, movement trends of entities evolv-ing over space and time and their connectivity across spatio-temporal and seman-tic dimensions. This paper presents a contribution based on a graph modeling for PoL that handles these dimensions.
Pattern of Life (PoL) is a common concept based on understanding the behaviour of a certain moving object, through analysing its past and present navigational patterns, for the purpose of potentially predicting its future actions.
Maritime Pattern of Life (PoL) aims at understanding and monitoring the behavioral patterns of a certain vessel to analyze and use for potentially predicting its future actions
We have been modeling an ever-increasing scale of applications with agents that simulate the pattern of life (PoL) and real-world human behaviors in diverse regions of the world. The goal is to support sociocultural training and analysis.
