Abstract: A risk management method, system, and non-transitory computer readable medium, include a data analyzing circuit configured to analyze user data, site data, and equipment data to map prior behavior types to an event on a site, a relationship determining circuit configured to determine a relationship between the mapped data and the event based on behaviors exhibited by the user and an impact on a performance factor and a risk factor, and a reinforcement learning circuit configured to use reinforcement learning to learn the performance factor to the risk factor ratio to optimize an overall site productivity.

Abstract: A reality augmenting computer-implemented method, system, and computer program product, includes detecting a consumer and at least one of a product and a location, determining a current sensory state of the consumer, calculating a desired sensory state to achieve a target mood based on a correlation between the target mood and a user model, and executing an action according to the desired sensory state by a wearable to change the current sensory state of the consumer to the target mood.

Abstract: A display control method, system, and non-transitory computer readable medium for a digital billboard display, include an attribute identification circuit configured to identify attributes of each user of a group of users viewing the digital billboard display, a content determining circuit configured to determine a content type to be displayed on the digital billboard based on an aggregation of all of the attributes of the group of users identified by the attribute identification circuit, and a display augmenting circuit configured to deliver the content type to the digital billboard display.

Abstract: A reality augmenting computer-implemented method, system, and computer program product, includes detecting a consumer and at least one of a product and a location, determining a current sensory state of the consumer, calculating a desired sensory state to achieve a target mood based on a correlation between the target mood and a user model, and executing an action according to the desired sensory state by a wearable to change the current sensory state of the consumer to the target mood.

Abstract: A risk management method, system, and non-transitory computer readable medium, include a data analyzing circuit configured to analyze user data, site data, and equipment data to map prior behavior types to an event on a site, a relationship determining circuit configured to determine a relationship between the mapped data and the event based on behaviors exhibited by the user and an impact on a performance factor and a risk factor, and a reinforcement learning circuit configured to use reinforcement learning to learn the performance factor to the risk factor ratio to optimize an overall site productivity.

Abstract: A display control method, system, and non-transitory computer readable medium for a digital billboard display, include an attribute identification circuit configured to identify attributes of each user of a group of users viewing the digital billboard display, a content determining circuit configured to determine a content type to be displayed on the digital billboard based on an aggregation of all of the attributes of the group of users identified by the attribute identification circuit, and a display augmenting circuit configured to deliver the content type to the digital billboard display.

Abstract: A method of optimizing equipment usage in a network includes determining wear of a first machine in the network. A state of a second machine in the network is determined. When the second machine will be available for use with the first machine is determined based on the state of the second machine. A state of the first machine is recorded. Optimal usage criteria for the first machine is determined based on when the second machine will be available, the recorded state of the first machine and the wear of the first machine. The optimal usage criteria is provided to the first machine. The first machine is monitored after its has received the optimal usage criteria.

Abstract: A system and method for collaborative vehicle crash planning employs a model-based approach for mitigating damage and injuries resulting from a vehicle collision. A real-time crash model is generated to determine an optimal crash sequence within a parallel computing environment.

Abstract: A system and method for collaborative vehicle crash planning employs a model-based approach for mitigating damage and injuries resulting from a vehicle collision. A real-time crash model is generated to determine an optimal crash sequence within a parallel computing environment.

Abstract: A system and method for collaborative vehicle crash planning employs a model-based approach for mitigating damage and injuries resulting from a vehicle collision. A real-time crash model is generated to determine an optimal crash sequence within a parallel computing environment.

Abstract: A system and method for collaborative vehicle crash planning employs a model-based approach for mitigating damage and injuries resulting from a vehicle collision. A real-time crash model is generated to determine an optimal crash sequence within a parallel computing environment.