Platforms and methods for improving correspondence of haptic output to sensor data
Platforms and methods for improving correspondence between sensor data and haptic output are disclosed. A platform may include a haptic user device and a data collection system to collect sensor data. The haptic user interface may provide different types of haptic stimulation to a user based on the sensor data. The data collection system has a cognitive input selection system with machine learning to improve the effectiveness of the haptic output to the user. The machine learning is trained on feedback of user behavior. The machine learning improves the effectiveness of the haptic output by determining which type of haptic simulation to provide such that the haptic output logically corresponds to the sensor data, or by determining to vary one or more of a timing, an intensity level, or a duration of the haptic output based on the sensor data.
1 . A haptic platform for monitoring an industrial environment, comprising:
a haptic user device including a data collection system and a haptic user interface;
the data collection system structured to collect industrial sensor data from a plurality of sensors operably connected to the industrial environment;
the haptic user interface structured to provide a plurality of types of haptic stimulation as haptic stimulation to a user based on the industrial sensor data; and
the data collection system including a cognitive input selection system having machine learning structured to improve an effectiveness of the haptic stimulation to the user,
wherein the machine learning is trained on user data received from at least one user sensor, by the cognitive input selection system, indicative of a user behavior response to a particular haptic stimulation, wherein the machine learning is further trained by varying the haptic stimulation based on industrial sensor data from a sensor, and at least one of: a type of the haptic stimulation, a timing of the haptic stimulation, an intensity level of the haptic stimulation, or a duration of the haptic stimulation, and
wherein the machine learning is structured to improve the effectiveness of the haptic stimulation by determining to vary one or more of: the type of the haptic stimulation, the timing of the haptic stimulation, the intensity level of the haptic stimulation, or the duration of the haptic stimulation based on the industrial sensor data, to influence a user behavior with respect to at least one of: a response, a system outcome, a data collection outcome, or an analytic outcome.
2 . The haptic platform of claim 1 , wherein the machine learning is structured to improve the effectiveness of the haptic stimulation by determining which of the plurality of types of haptic simulation to provide as the haptic stimulation such that the haptic stimulation logically corresponds to the industrial sensor data.
3 . The haptic platform of claim 2 , wherein the plurality of types of haptic stimulation includes at least two of a vibration stimulation, a heat stimulation, an electrical stimulation, or a sound stimulation.
4 . The haptic platform of claim 3 , wherein the plurality of types of haptic stimulation includes the vibration stimulation, and the machine learning determines to provide the vibration stimulation as the haptic stimulation when the industrial sensor data indicates an alarm condition indicated by a vibration in the industrial environment.
5 . The haptic platform of claim 4 , wherein the plurality of types of haptic stimulation further includes the heat stimulation, and the machine learning determines to provide the heat stimulation as the haptic stimulation when the industrial sensor data indicates an alarm condition indicated by thermal data in the industrial environment.
6 . The haptic platform of claim 1 , further comprising:
a learning feedback system, wherein the learning feedback system provides the user data indicative of the user behavior response to the cognitive input selection system.
7 . The haptic platform of claim 1 , further comprising:
the plurality of sensors operably connected to the industrial environment.
8 . The haptic platform of claim 1 , wherein the haptic stimulation provides an intuitive alert to the user.
9 . The haptic platform of claim 1 , wherein the haptic user device is wearable by the user.
10 . The haptic platform of claim 1 , wherein the user data indicative of the user behavior response includes at least one of a real world response to haptic feedback or a result of simulation and testing of user behavior.
11 . The haptic platform of claim 1 , wherein the haptic user interface is structured to provide the haptic stimulation to the user when the industrial sensor data indicates an alarm condition in the industrial environment.
12 . A method of providing haptic feedback for an industrial environment, the method comprising:
collecting, by a data collection system, industrial sensor data from a plurality of sensors operably connected to the industrial environment;
training a machine learning based on user data received from at least one user sensor, by the data collection system, indicative of a user behavior response to a haptic stimulation, wherein the machine learning is further trained by varying the haptic stimulation based on industrial sensor data from at least a subset of the plurality of sensors, and at least one of: a type of a plurality of types of haptic stimulation, a timing of haptic stimulation, an intensity level of haptic stimulation, or a duration of haptic stimulation;
improving, by the machine learning, an effectiveness of a haptic stimulation by determining to vary one or more of a type of haptic stimulation, a timing of haptic stimulation, an intensity level of haptic stimulation, or a duration of haptic stimulation based on the industrial sensor data, to influence a user behavior with respect to at least one of a response, a system outcome, a data collection outcome, or an analytic outcome; and
providing the haptic stimulation to the user.
13 . The method of claim 12 , wherein the plurality of types of haptic stimulation includes at least two of a vibration stimulation, a heat stimulation, an electrical stimulation, or a sound stimulation.
14 . The method of claim 13 , wherein the plurality of types of haptic stimulation includes the vibration stimulation, and the machine learning determines to provide the vibration stimulation as the haptic stimulation when the industrial sensor data indicates an alarm condition indicated by a vibration in the industrial environment.
15 . The method of claim 14 , wherein the plurality of types of haptic stimulation further includes the heat stimulation, and the machine learning determines to provide the heat stimulation as the haptic stimulation when the industrial sensor data indicates an alarm condition indicated by thermal data in the industrial environment.
16 . The method of claim 12 , wherein the haptic stimulation provides an intuitive alert to the user.
17 . The method of claim 12 , wherein the user data indicative of the user behavior response includes at least one of a real world response to haptic stimulation or a result of simulation and testing of user data indicative of a user behavior.
18 . The method of claim 12 , wherein providing the haptic stimulation to the user further comprises:
providing the haptic stimulation to the user when the industrial sensor data indicates an alarm condition in the industrial environment.
19 . A non-transitory computer-readable storage medium storing computer executable instructions that, when executed, cause at least one processor to perform actions comprising:
collecting industrial sensor data from a plurality of sensors operably connected to an industrial environment;
training machine learning based on user data received from at least one user sensor, indicative of a user behavior in response to a haptic stimulation, wherein the training further includes varying the haptic stimulation based on industrial sensor data from at least one of the plurality of sensors, wherein the training further includes varying the haptic stimulation based on industrial sensor data, and at least one of: a type of a plurality of types of haptic stimulation, a timing of haptic stimulation, an intensity level of haptic stimulation, or a duration of haptic stimulation;
improving, using the machine learning, an effectiveness of a haptic stimulation by using the machine learning to determine to vary one or more of a timing, an intensity level, or a duration of the haptic stimulation based on the industrial sensor data, to influence a user behavior with respect to at least one of a response, a system outcome, a data collection outcome, or an analytic outcome; and
instructing a haptic device to provide the haptic stimulation to the user.
20 . The non-transitory computer-readable storage medium of claim 19 , wherein the plurality of types of haptic stimulation includes at least two of a vibration stimulation, a heat stimulation, an electrical stimulation, or a sound stimulation.