Abstract:
Embodiments of the present invention disclose a method, computer program product, and system for generating and transmitting a Personalized Emergency Evacuation Plan (PEEP). The computer receives an emergency condition real-time data from a plurality of building sensors, a tracking data of at least one user from a plurality of tracking sensors, a facility structural data from a facility database, and a stored user data from a user database for the at least one user. The computer generates a personalized emergency evacuation plan (PEEP) for the at least one user, wherein is a set of recommendations to put the user in the safest position, based on at least the emergency condition real-time data and the received stored user data. The computer transmits the PEEP to a user mobile device, wherein the user mobile device presents the PEEP to the at least one user.
Abstract:
Travel itineraries are automatically prepared based upon user interests and sentiments inferred by deep semantic analysis of user-commented and user-preferred digital works of literature by receiving interests and associated sentiment levels for at least one user according to a deep semantic analysis of a plurality of works of literature, wherein the works of literature have been rated, commented, or both rated and commented by the user; searching repositories of travel items to find one or more matching travel items to the received more interests and associated sentiment levels; and preparing at least one travel itinerary including at least one found matching travel item. Travel itineraries may be prepared responsive to a user-initiated trip planning session, responsive to notification of a new travel item's availability, periodically, or a combination thereof.
Abstract:
An embodiment for dynamically tuning system configuration settings across multiple systems using hypothetical configuration analysis. The embodiment may gather input data for a target system, the input data including configuration settings data, a series of configuration setting parameters, and telemetry data. The embodiment may generate, from the input data, a machine learning model configured to process network data and the configuration settings data from the target system. The embodiment may determine dependencies between a given parameter from the series of configuration setting parameters and a given resource from a series of resources using the generated machine learning model. The embodiment may further predict, using the generated machine learning model, and based on the determined dependencies, performance outcomes under a tuneable range of the series of configuration setting parameters. The embodiment may generalize the generated machine learning model across a plurality of secondary systems.
Abstract:
Techniques are described with respect to a system, method, and computer product for generating relevance alerts. An associated method includes analyzing a multi-party discussion based on a generated profile associated with a user and assigning at least one relevance value associated with the user to the multi-party discussion based on the analysis and an amount of multi-party discussion participation associated with the user. The method further includes generating an alert for the user to participate in the multi-party discussion in response to determining the relevance value exceeding a relevance threshold associated with the multi-party discussion.
Abstract:
Techniques are described with respect to a system, method, and computer product for generating relevance alerts. An associated method includes analyzing a multi-party discussion based on a generated profile associated with a user and assigning at least one relevance value associated with the user to the multi-party discussion based on the analysis and an amount of multi-party discussion participation associated with the user. The method further includes generating an alert for the user to participate in the multi-party discussion in response to determining the relevance value exceeding a relevance threshold associated with the multi-party discussion.
Abstract:
Embodiments of the present invention disclose a method, computer program product, and system for generating and transmitting a Personalized Emergency Evacuation Plan (PEEP). The computer receives an emergency condition real-time data from a plurality of building sensors, a tracking data of at least one user from a plurality of tracking sensors, a facility structural data from a facility database, and a stored user data from a user database for the at least one user. The computer generates a personalized emergency evacuation plan (PEEP) for the at least one user, wherein is a set of recommendations to put the user in the safest position, based on at least the emergency condition real-time data and the received stored user data. The computer transmits the PEEP to a user mobile device, wherein the user mobile device presents the PEEP to the at least one user.
Abstract:
Embodiments of the present invention disclose a method, computer program product, and system for generating and transmitting a Personalized Emergency Evacuation Plan (PEEP). The computer receives an emergency condition real-time data from a plurality of building sensors, a tracking data of at least one user from a plurality of tracking sensors, a facility structural data from a facility database, and a stored user data from a user database for the at least one user. The computer generates a personalized emergency evacuation plan (PEEP) for the at least one user, wherein is a set of recommendations to put the user in the safest position, based on at least the emergency condition real-time data and the received stored user data. The computer transmits the PEEP to a user mobile device, wherein the user mobile device presents the PEEP to the at least one user.