Modeling Human Behavior in Work Environment Using Neural Networks

20220366244

17/761396

September 30, 2019

A system and method for modeling human behavior includes receiving, by a classifier module, sensor data from one or more sensors monitoring human behavior associated with a work task and to identify the type of human behavior based on a trained neural network. A prediction module receives the identified type of human behavior from the classifier and generates prediction data representing predicted next one or more human actions based on a time series of position vectors learned by the trained neural network. A rendering module translates the prediction data into a visual rendering for a virtual human simulation model.

1. A system for modeling human behavior, comprising: a processor; and a computer readable medium having stored thereon a set of modules executable by the processor, the modules comprising: a classification module configured to receive sensor data from one or more sensors monitoring human behavior associated with a work task and to identify the type of human behavior based on a trained neural network; a prediction module configured to receive the identified type of human behavior from the classifier and to generate prediction data representing predicted next one or more human actions based on a time series of position vectors learned by the trained neural network; and a rendering module for translating the prediction data into a visual rendering for a virtual human simulation model.

2. The system of claim 1, wherein the position vectors of the trained neural network represents elements of human body positions in a time sequence.

3. The system of claim 1, wherein the position vectors include environmental parameters and situation parameters associated with the monitored human activity.

4. The system of claim 1, wherein the position vectors include data fields for gender, body size, and experience for the monitored work task.

5. The system of claim 1, further comprising: an alert module configured to signal an alert based on the prediction data in response to determining that next one or more human actions is likely to produce a human injury or damage to work equipment.

6. The system of claim 1, further comprising: an analysis module configured to rank predicted behavior states of work production, work safety, ergonomic scores, or a combination thereof using the trained neural network tuned to simulated environment and situation parameters so that parameter weights correspond to a new problem having a proposed environment and situation, wherein the trained neural network is fed inputs including sets of human factors and a query to predict how a virtual human will behave.

7. The system of claim 6, wherein the analysis module is further configured to perform analysis of the ranked scores to develop an optimized work station configuration.

8. A computer-based method for modeling human behavior, comprising: receiving, by a classification module, sensor data from one or more sensors monitoring human behavior associated with a work task and to identify the type of human behavior based on a trained neural network; receiving, by a prediction module, the identified type of human behavior from the classifier and to generate prediction data representing predicted next one or more human actions based on a time series of position vectors learned by the trained neural network; and translating, by a rendering module, the prediction data into a visual rendering for a virtual human simulation model.

9. The method of claim 8, wherein the position vectors of the trained neural network represents elements of human body positions in a time sequence.

10. The method of claim 8, wherein the position vectors include environmental parameters and situation parameters associated with the monitored human activity.

11. The method of claim 8, wherein the position vectors include data fields for gender, body size, and experience for the monitored work task.

12. The method of claim 8, further comprising: signaling, by an alert module, an alert based on the prediction data in response to determining that next one or more human actions is likely to produce a human injury or damage to work equipment.

13. The method of claim 8, further comprising: ranking, by an analysis module, predicted behavior states of work production, work safety, ergonomic scores, or a combination thereof using the trained neural network tuned to simulated environment and situation parameters so that parameter weights correspond to a new problem having a proposed environment and situation, wherein the trained neural network is fed inputs including sets of human factors and a query to predict how a virtual human will behave.

14. The method of claim 13, further comprising: performing, by the analysis module, analysis of the ranked scores to develop an optimized work station configuration.

15. The method of claim 8, wherein the neural network is trained using machine state and environmental condition data collected by various sensors, wherein the neural network training includes deriving a situational awareness driven model by annotating predicted situations based on similarity of complexity and dynamics between known and unknown situations.

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