| CPC G06Q 10/0635 (2013.01) [G06Q 10/04 (2013.01); G06Q 10/0631 (2013.01)] | 13 Claims |
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1. A method, comprising:
continuously capturing one or more pieces of internal data for an entity about a workplace hazard and one or more pieces of external data about the workplace hazard for the entity that together form a plurality of dynamic data points for the workplace hazard risk of the entity wherein each of the plurality of dynamic data points is a data point to grade risk and predict probability of an injury from the workplace hazard for the entity;
continuously introducing the continuously captured dynamic data points into a plurality of compliance modules;
processing the continuously captured dynamic data points by each of the plurality of compliance modules that generate a safety compliance factor that assesses a compliance of the entity for workplace risk based on the continuously captured dynamic data points, a safety behavior factor that assesses a set of behaviors of the entity for workplace risk against a similar sized company and a module significance factor that assesses a significance of the particular compliance module relative to a workplace hazard incident probability and wherein each compliance module generates a safety factor;
performing, using a recursive machine learning process executed by a processor of a computer system, a scoring process to generate an evolving risk score of the probability and severity of the workplace hazard for the entity based on the safety factors for each of the compliance modules for the entity and weighing all of the safety factors for all of the compliance modules, the evolving risk score is updated when more continuously captured dynamic data points are introduced; and
generating, by the processor of the computer system, a user interface that displays the evolving risk score to an authorized user of the entity.
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