Abstract: A method and system are provided. The method includes performing, by at least a computer processing system having a hardware processor, a particulate mapping process to predict particulate exposure at a target location based on an estimated particulate source, an estimated particulate source output, and a fine-grained weather forecast for the target location. The performing step includes estimating the target location using a fine-grained weather hindcast and inverse modelling. The performing step further includes generating observations of particulate exposure for one or more specific particulates, using a set of particulate sensors.

Abstract: A method of avoiding harmful noise levels, the method comprising implementing a cognitive suite of workplace hygiene and injury predictors (WHIP) that has learned to identify noise sources and indicators of harmful noise levels, detecting an indicator, and implementing a corrective action by at least one of altering the operation of a noise source, modifying a time of a scheduled task, or changing prescribed personal protective equipment.

Abstract: Solar irradiation may be predicted based on input terrestrial sky images comprising cloud images, the terrestrial sky images taken from a plurality of geographic locations by a plurality of devices; for example, wherein the terrestrial sky images are crowd sourced from the plurality of devices. A model may be generated that predicts solar irradiation in a geographic area based on the input terrestrial sky images and the geographic locations from where the terrestrial sky images were taken. A signal representing the solar irradiation predicted by the model is output.

Abstract: Training a machine to provide specialized health care apparatus may include receiving text describing a user's health condition via a user interface. Text may be converted into corresponding medical terms. A database may be searched for a list of health care providers treating health conditions associated with the medical terms. A machine learning model may be built that may include user preference for a predefined set of features associated with the user's health condition and health care provider preference for the predefined set of features in treating the user's health condition. The machine learning model may predict one or more of the health care providers that provide treatment for the user's health condition that matches the user's preference. The machine learning model may be retrained based on one or more of feedback from the user, the health care providers, and updated traits of the users and the health care providers.

Abstract: Ultraviolet light poses both health benefits and health risks. A method, device and computer storage program balances the health risks and benefits of ultraviolet light exposure with personal sensitivities and preferences for these health risks and benefits. An ultraviolet light exposure level of a subject person is estimated by monitoring data from a plurality of sources. A personal sensitivity to ultraviolet light exposure is also estimated from data from various sources. A recommendation for the subject person is generated based upon the estimated risks and benefits of ultraviolet light exposure.

Abstract: A target space having configurable parameters may be defined such that nodes of a corresponding social network may be adapted to an elastic map of the target space. Communications may be directed to one or more nodes of the social network based on the computed elastic map.

Abstract: The present disclosure relates generally to the field of dynamic risk assessment (e.g., with respect to insurance claims). In one specific example, mechanisms are provided for dynamically assessing the presence or absence of people and/or insured items of value in an insured location (e.g., an insured home). In various embodiments, systems, methods and computer program products are provided.

Abstract: Methods and systems for predicting injury risk include generating state sequences that precede a hazard event based on information regarding a user's state. A cognitive suite of workplace hygiene and injury predictors (WHIP) is generated based on the state sequences using a processor, wherein the cognitive WHIP predicts a degree of risk correlated with each particular user state sequence. A risk heat map of a workplace is generated based on the cognitive WHIP that encodes regions of greater and lesser risk. An ameliorative action is triggered when a user moves into an area of high risk based on the heat map.

Abstract: Embodiments include method, systems and computer program products to generate optimal team configuration recommendations. In some embodiments, parameters and project data associated with a project may be received. Employee data may be received from one or more sources. The employee data, the project data, and the parameters associated with the project may be analyzed. A team-member compatibility matrix may be generated using cognitive analysis based on the analyzed employee data, the project data, and the parameters associated with the project. Optimal and para-optimal team configurations may be calculated using the team-member compatibility matrix. A team configuration recommendation may be generated using the optimal and para-optimal team configurations. The team configuration recommendation may be transmitted.

Abstract: A method of avoiding harmful noise levels, the method comprising implementing a cognitive suite of workplace hygiene and injury predictors (WHIP) that has learned to identify noise sources and indicators of harmful noise levels, detecting an indicator, and implementing a corrective action by at least one of altering the operation of a noise source, modifying a time of a scheduled task, or changing prescribed personal protective equipment.

Abstract: A method of avoiding harmful chemical emission concentration levels, the method comprising implementing a cognitive suite of workplace hygiene and injury predictors (WHIP) that has learned to identify chemical emission sources and indicators of harmful chemical emission concentration levels, detecting an indicator, and implementing a corrective action by at least one of altering the operation of a chemical emissions source, modifying a time of a scheduled task, or changing prescribed personal protective equipment.

Abstract: Training a machine to provide specialized health care apparatus may include receiving text describing a user's health condition via a user interface. Text may be converted into corresponding medical terms. A database may be searched for a list of health care providers treating health conditions associated with the medical terms. A machine learning model may be built that may include user preference for a predefined set of features associated with the user's health condition and health care provider preference for the predefined set of features in treating the user's health condition. The machine learning model may predict one or more of the health care providers that provide treatment for the user's health condition that matches the user's preference. The machine learning model may be retrained based on one or more of feedback from the user, the health care providers, and updated traits of the users and the health care providers.

Abstract: Technical solutions are described for verifying attendance at an alarm event. An example method includes receiving a registration of the alarm event, where the registration identifies an alarm device associated with the alarm event, and a location of the alarm event. The method also includes in response to the occurrence of the alarm, sending an alarm message to a user apparatus, where the user apparatus is within a predetermined vicinity of the location. The method also includes, in response to receiving an attendance message from the user apparatus, validating the attendance message based on predetermined conditions, where the predetermined conditions verify that the attendance message was transmitted within a predetermined expiration time and sending a reward message in response to the attendance message being valid.

Abstract: Described herein is a method for alerting of personal risk in the workplace through a wearable indication signifying a risk condition that includes generating a set of workplace predictors of risk relating to accidents, injury, and industrial hygiene, based on at least one worker state that includes at least one of a physical state, a cognitive state, and an emotional state, and alerting a worker endangered by a predicted elevated risk to the existence of the predicted elevated risk by sending a perceivable alert to the worker. A system for alerting of personal workplace risk is also described.

Abstract: A method, system, and computer program product to perform image-based estimation of a risk of a vehicle having a specified status include receiving images from one or more cameras, obtaining one or more vehicle images of the vehicle from the image, classifying the vehicle based on the one or more vehicle images to determine a vehicle classification, extracting features from the one or more vehicle images based on the vehicle classification, and comparing the features with risk indicators to determine estimation of the risk. Instructions are provided for an action based on the risk.

Abstract: A method and system are provided. The method includes generating a set of workplace predictors of risk relating to accidents, injury, and industrial hygiene, based on at least one employee state that includes at least one of a physical state, a cognitive state, and an emotional state. The method further includes modifying a behavior of a workplace machine by causing a modification to the workplace machine that changes or limits the behavior of the workplace machine, responsive to the set of workplace predictors.

Abstract: Embodiments are directed to a computer implemented counterproductive interaction identification system. The system includes an electronic tool configured to hold data of a user, and an analyzer circuit configured to derive a cognitive trait of the user based at least in part on the data of the user. The system further includes a decision engine configured to determine, based at least in part on the derived cognitive trait of the user, that the user is a target or a source of an actual or an impending counterproductive interaction.

Abstract: Embodiments are directed to a computer implemented counterproductive interaction identification system. The system includes an electronic tool configured to hold data of a user, and an analyzer circuit configured to derive a cognitive trait of the user based at least in part on the data of the user. The system further includes a decision engine configured to determine, based at least in part on the derived cognitive trait of the user, that the user is a target or a source of an actual or an impending counterproductive interaction.

Abstract: An information processing system, computer readable storage medium, and methods for analyzing the airflow related health of a person. A method includes obtaining an audio sample of a person's verbal communication, obtaining geographic information of the person, querying a remote server based on the geographic information, and obtaining additional information from the remote server, the additional information being related to the geographic information, and extracting contours of amplitude change from the at least one audio sample over a period of time, the contours of amplitude change corresponding to changes in an airflow profile of the person. The method further includes correlating the contours of amplitude change with periodic episodes typical of airflow related health problems, and determining, based at least on the additional information, whether the contours of amplitude change result from at least one local environmental factor related to the geographic information.

Abstract: Described herein is a method for alerting of personal risk in the workplace through a wearable indication signifying a risk condition that includes generating a set of workplace predictors of risk relating to accidents, injury, and industrial hygiene, based on at least one worker state that includes at least one of a physical state, a cognitive state, and an emotional state, and alerting a worker endangered by a predicted elevated risk to the existence of the predicted elevated risk by sending a perceivable alert to the worker. A system for alerting of personal workplace risk is also described.