Context-aware wearable safety system

1. A method comprising:

receiving, at a rules engine executable by one or more processors, biometric data from one or more body sensors monitoring a user;

receiving, at the rules engine, environmental data from one or more environmental sensors in an area surrounding the user;

retrieving, from a server, activity information associated with the user;

determining, at the rules engine, an activity being performed by the user based on the activity information;

assigning, at the rules engine, weights to the biometric data and the environmental data, the weights assigned to the biometric data being different than the weight assigned to the environmental data, the weights assigned based on the task currently being performed by the user;

calculating, at the rules engine, a current safety score for the worker using the assigned weights as coefficients to variables, the variables being values obtained from the biometric data and the environmental data;

comparing, at the rules engine, the current safety score with a reference safety score; and

based on the comparing, generating, at the rules engine, a safety indicator.

2. The method of claim 1 , wherein the safety value is a safety threshold, and the safety indicator is an alert to indicate that the safety threshold has been reached.

3. The method of claim 1 , further comprising:

wirelessly sending the safety indicator to smart glasses worn by the user.

4. The method of claim 1 , further comprising:

wirelessly sending the safety indicator to a wearable computer worn by the user.

5. The method of claim 1 , wherein the activity information includes user health information; and

wherein the weights are further based on the user health information, thus personalizing the weights for individual user health conditions.

6. The method of claim 1 , wherein the environmental data includes information from a Radio Frequency ID (RFID) scanner on a machine, the environmental data identifying a tool having an embedded RFID chip that has been passed next to the RFID scanner, the method further comprising verifying that the worker is performing the task via the information from the RFID scanner.

7. The method of claim 1 , wherein the assigned weights are stored in a multidimensional data structure in a database, the multidimensional data structure having a plurality of axes each corresponding to a different task category type and an axis corresponding to body and environmental sensor type, with values stored in the multidimensional data structure corresponding to the assigned weights.

8. A system comprising:

a server containing activity information for the user;

a rules engine executable by one or more processors and configured to:

receive, at a rules engine executable by one or more processors, biometric data from one or more body sensors operatively monitoring a user;

receive, at the rules engine, environmental data from one or more environmental sensors in an area operatively surrounding the user;

retrieve, from a server, activity information associated with the user;

determine, at the rules engine, an activity being performed by the user based on the activity information;

assign, at the rules engine, weights to the biometric data and the environmental data, the weights assigned to the biometric data being different than the weight assigned to the environmental data, the weights assigned based on the task operatively being performed by the user;

calculate, at the rules engine, a current safety score for the worker using the assigned weights as coefficients to variables, the variables being values obtained from the biometric data and the environmental data;

compare, at the rules engine, the current safety score with a reference safety score; and

based on the comparing, generate, at the rules engine, a safety indicator.

9. The system of claim 8 , wherein the safety value is a safety threshold, and the safety indicator is an alert to indicate that the safety threshold has been reached.

10. The system of claim 8 , the rules engine further configured to:

wirelessly send the alert to smart glasses worn by the worker.

11. The system of claim 8 , the rules engine further configured to:

wirelessly send the alert to a wearable computer worn by the user.

12. The system of claim 8 , wherein the activity information includes user health information; and

wherein the weights are further based on the user health information, thus personalizing the weights for individual user health conditions.

13. The system of claim 8 , wherein the environmental data includes information from a Radio Frequency ID (RFID) scanner on a machine, the environmental data identifying a tool having an embedded RFID chip that has been passed next to the RFID scanner, the rules engine further configured to verify that the worker is performing the task via the information from the RFID scanner.

14. The system of claim 8 , wherein the assigned weights are stored in a multidimensional data structure in a database, the multidimensional data structure having a plurality of axes each corresponding to a different task category type and an axis corresponding to body and environmental sensor type, with values stored in the multidimensional data structure corresponding to the assigned weights.

15. A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations, the operations comprising:

receiving biometric data from one or more body sensors monitoring a worker;

receiving, at a rules engine executable by one or more processors, biometric data from one or more body sensors monitoring a user;

receiving, at the rules engine, environmental data from one or more environmental sensors in an area surrounding the user;

retrieving, from a server, activity information associated with the user;

determining, at the rules engine, an activity being performed by the user based on the activity information;

assigning; at the rules engine, weights to the biometric data and the environmental data, the weights assigned to the biometric data being different than the weight assigned to the environmental data, the weights assigned based on the task currently being performed by the user;

calculating, at the rules engine, a current safety score for the worker using the assigned weights as coefficients to variables, the variables being values obtained from the biometric data and the environmental data;

comparing, at the rules engine, the current safety score with a reference safety score; and

based on the comparing, generating, at the rules engine, a safety indicator.

16. The non-transitory machine-readable storage medium of claim 15 , wherein the safety value is a safety threshold, and the safety indicator is an alert to indicate that the safety threshold has been reached.

17. The non-transitory machine-readable storage medium of claim 15 , the operations further comprising:

wirelessly sending the alert to smart glasses worn by the worker.

18. The non-transitory machine-readable storage medium of claim 15 , the operations further comprising:

wirelessly sending the alert to a wearable computer worn by the user.

19. The non-transitory machine-readable storage medium of claim 15 , wherein the activity information includes user health information; and

wherein the weights are further based on the user health information, thus personalizing the weights for individual user health conditions.

20. The non-transitory machine-readable storage medium of claim 15 , wherein the assigned weights are stored in a multidimensional data structure in a database, the multidimensional data structure having a plurality of axes each corresponding to a different task category type and an axis corresponding to body and environmental sensor type, with values stored in the multidimensional data structure corresponding to the assigned weights.