Risk detection and peer corrective assistance for risk mitigation within a work environment

A computer readable storage medium comprising a computer readable program for predicting injury risk, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:

• generating state sequences that precede a hazard event that poses a risk of workplace injury based on information regarding user states by embedding a relatively high-dimensional measurement of the user's state in a relatively low-dimensional feature space;
• generating a cognitive suite of workplace hygiene and injury predictors (WHIP) based on the state sequences using a processor, wherein the cognitive WHIP predicts a degree of risk of workplace injury correlated with each particular user state sequence;
• determining an advantageous relationship between a user and one or more socially connected users;
• determining an outcome of a previous ameliorative action;
• triggering an ameliorative action responsive to the user entering a high-risk area determined based on the user's state including an indication of user drowsiness, based on the advantageous relationship to the one or more socially connected users, the outcome of the previous ameliorative action, and proximity of the user to one or more other users, including providing an incentive to the one or more socially connected users to reduce the degree of risk;
• and
• triggering an automatic change in a setting of a device in a vicinity of the user in the high-risk state to reduce a degree of risk.

A system for predicting injury risk, comprising:

• a processor;
• a memory;
• a cognitive suite of workplace hygiene and injury predictors (WHIP) module that is stored in the memory and executed by the processor, configured to generate state sequences that precede a hazard event that poses a risk of workplace injury based on information regarding user states by embedding a relatively high-dimensional measurement of the user states in a relatively low-dimensional feature space and to generate a cognitive WHIP based on the state sequences, wherein the cognitive WHIP predicts a degree of risk of workplace injury correlated with each particular user state sequence;
• a social network module that is stored in the memory and executed by the processor, configured to determine an advantageous relationship between a user and one or more socially, connected users;
• and
• an alert module that is stored in the memory and executed by the processor, configured determine an outcome of a previous ameliorative action, to trigger an ameliorative action responsive to the user moving into a high risk area determined based on the user's state7 including an indication of user drowsiness, based on the advantageous relationship to the one or more socially connected users, the outcome of the previous ameliorative action, and proximity of the user to one or more other users, including providing an incentive to the one or more socially connected users to reduce the degree of risk, and further configured to trigger an automatic change in a setting of a device in a vicinity of the user in the high-risk area to reduce a degree of risk.